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Editors: Marina Meila, Tong Zhang
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A New Representation of Successor Features for Transfer across Dissimilar Environments
; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1-9
Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan K. Yadav; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10-20
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Debiasing Model Updates for Improving Personalized Federated Training
Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:21-31
Memory Efficient Online Meta Learning
Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:32-42
Robust Testing and Estimation under Manipulation Attacks
Jayadev Acharya, Ziteng Sun, Huanyu Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:43-53
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GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:54-65
f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:66-75
Towards Rigorous Interpretations: a Formalisation of Feature Attribution
Darius Afchar, Vincent Guigue, Romain Hennequin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:76-86
Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:87-99
A Regret Minimization Approach to Iterative Learning Control
Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:100-109
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:110-119
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Label Inference Attacks from Log-loss Scores
Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:120-129
Deep kernel processes
Laurence Aitchison, Adam Yang, Sebastian W. Ober; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:130-140
How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation
Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:141-151
On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:152-162
Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
Maxwell M Aladago, Lorenzo Torresani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:163-174
A large-scale benchmark for few-shot program induction and synthesis
Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Joshua Tenenbaum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:175-186
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Robust Pure Exploration in Linear Bandits with Limited Budget
Ayya Alieva, Ashok Cutkosky, Abhimanyu Das; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:187-195
Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:196-206
Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions
Pierre Alquier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:207-218
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolò Fusi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:219-230
Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Georgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:231-242
Safe Reinforcement Learning with Linear Function Approximation
Sanae Amani, Christos Thrampoulidis, Lin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:243-253
Automatic variational inference with cascading flows
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:254-263
Sparse Bayesian Learning via Stepwise Regression
Sebastian E. Ament, Carla P. Gomes; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:264-274
Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards
Susan Amin, Maziar Gomrokchi, Hossein Aboutalebi, Harsh Satija, Doina Precup; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:275-285
Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:286-296
Unitary Branching Programs: Learnability and Lower Bounds
Fidel Ernesto Diaz Andino, Maria Kokkou, Mateus De Oliveira Oliveira, Farhad Vadiee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:297-306
The Logical Options Framework
Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan Decastro, Micah Fry, Daniela Rus; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:307-317
Annealed Flow Transport Monte Carlo
Michael Arbel, Alex Matthews, Arnaud Doucet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:318-330
Permutation Weighting
David Arbour, Drew Dimmery, Arjun Sondhi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:331-341
Analyzing the tree-layer structure of Deep Forests
Ludovic Arnould, Claire Boyer, Erwan Scornet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:342-350
Dropout: Explicit Forms and Capacity Control
Raman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:351-361
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients
Artem Artemev, David R. Burt, Mark van der Wilk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:362-372
Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam, Benjamin Van Roy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:373-382
Private Adaptive Gradient Methods for Convex Optimization
Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:383-392
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:393-403
Combinatorial Blocking Bandits with Stochastic Delays
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:404-413
Dichotomous Optimistic Search to Quantify Human Perception
Julien Audiffren; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:414-424
Federated Learning under Arbitrary Communication Patterns
Dmitrii Avdiukhin, Shiva Kasiviswanathan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:425-435
Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge
Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:436-445
Decomposable Submodular Function Minimization via Maximum Flow
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:446-456
Differentially Private Query Release Through Adaptive Projection
Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit A. Siva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:457-467
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:468-477
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:478-489
Uniform Convergence, Adversarial Spheres and a Simple Remedy
Gregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:490-499
Faster Kernel Matrix Algebra via Density Estimation
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:500-510
Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees
Kishan Panaganti Badrinath, Dileep Kalathil; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:511-520
Skill Discovery for Exploration and Planning using Deep Skill Graphs
Akhil Bagaria, Jason K Senthil, George Konidaris; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:521-531
Locally Adaptive Label Smoothing Improves Predictive Churn
Dara Bahri, Heinrich Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:532-542
How Important is the Train-Validation Split in Meta-Learning?
Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:543-553
Stabilizing Equilibrium Models by Jacobian Regularization
Shaojie Bai, Vladlen Koltun, Zico Kolter; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:554-565
Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
Yu Bai, Song Mei, Huan Wang, Caiming Xiong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:566-576
Principled Exploration via Optimistic Bootstrapping and Backward Induction
Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:577-587
GLSearch: Maximum Common Subgraph Detection via Learning to Search
Yunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:588-598
Breaking the Limits of Message Passing Graph Neural Networks
Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:599-608
Instance Specific Approximations for Submodular Maximization
Eric Balkanski, Sharon Qian, Yaron Singer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:609-618
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Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment
Philip J Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:619-629
Regularized Online Allocation Problems: Fairness and Beyond
Santiago Balseiro, Haihao Lu, Vahab Mirrokni; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:630-639
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:640-650
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:651-661
Compositional Video Synthesis with Action Graphs
Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:662-673
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Approximating a Distribution Using Weight Queries
Nadav Barak, Sivan Sabato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:674-683
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:684-693
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
Burak Bartan, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:694-704
Beyond $log^2(T)$ regret for decentralized bandits in matching markets
Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:705-715
Optimal Thompson Sampling strategies for support-aware CVaR bandits
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:716-726
On Limited-Memory Subsampling Strategies for Bandits
Dorian Baudry, Yoan Russac, Olivier Cappé; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:727-737
Generalized Doubly Reparameterized Gradient Estimators
Matthias Bauer, Andriy Mnih; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:738-747
Directional Graph Networks
Dominique Beaini, Saro Passaro, Vincent Létourneau, Will Hamilton, Gabriele Corso, Pietro Lió; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:748-758
Policy Analysis using Synthetic Controls in Continuous-Time
Alexis Bellot, Mihaela van der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:759-768
Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Gordon Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:769-779
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer
Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:780-791
Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis
Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:792-802
Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan Noiry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:803-812
Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:813-824
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:825-836
Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:837-851
Principal Bit Analysis: Autoencoding with Schur-Concave Loss
Sourbh Bhadane, Aaron B Wagner, Jayadev Acharya; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:852-862
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Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:863-873
Additive Error Guarantees for Weighted Low Rank Approximation
Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:874-883
Sample Complexity of Robust Linear Classification on Separated Data
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:884-893
Finding k in Latent $k-$ polytope
Chiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:894-903
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction
Hangrui Bi, Hengyi Wang, Chence Shi, Connor Coley, Jian Tang, Hongyu Guo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:904-913
TempoRL: Learning When to Act
André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:914-924
Follow-the-Regularized-Leader Routes to Chaos in Routing Games
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski, Michał Misiurewicz, Georgios Piliouras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:925-935
Neural Symbolic Regression that scales
Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurelien Lucchi, Giambattista Parascandolo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:936-945
Model Distillation for Revenue Optimization: Interpretable Personalized Pricing
Max Biggs, Wei Sun, Markus Ettl; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:946-956
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Scalable Normalizing Flows for Permutation Invariant Densities
Marin Biloš, Stephan Günnemann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:957-967
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Online Learning for Load Balancing of Unknown Monotone Resource Allocation Games
Ilai Bistritz, Nicholas Bambos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:968-979
Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision
Johan Björck, Xiangyu Chen, Christopher De Sa, Carla P Gomes, Kilian Weinberger; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:980-991
Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:992-1004
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1005-1014
Black-box density function estimation using recursive partitioning
Erik Bodin, Zhenwen Dai, Neill Campbell, Carl Henrik Ek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1015-1025
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F Montufar, Pietro Lió, Michael Bronstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1026-1037
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning
Roberto Bondesan, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1038-1048
Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, William Whitney, Rajesh Ranganath, Joan Bruna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1049-1058
High-Performance Large-Scale Image Recognition Without Normalization
Andy Brock, Soham De, Samuel L Smith, Karen Simonyan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1059-1071
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Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo
James Brofos, Roy R Lederman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1072-1081
Reinforcement Learning of Implicit and Explicit Control Flow Instructions
Ethan Brooks, Janarthanan Rajendran, Richard L Lewis, Satinder Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1082-1091
Machine Unlearning for Random Forests
Jonathan Brophy, Daniel Lowd; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1092-1104
Value Alignment Verification
Daniel S Brown, Jordan Schneider, Anca Dragan, Scott Niekum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1105-1115
Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David A Bruns-Smith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1116-1126
Narrow Margins: Classification, Margins and Fat Tails
Francois Buet-Golfouse; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1127-1135
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Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1136-1146
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Disambiguation of Weak Supervision leading to Exponential Convergence rates
Vivien A Cabannnes, Francis Bach, Alessandro Rudi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1147-1157
Finite mixture models do not reliably learn the number of components
Diana Cai, Trevor Campbell, Tamara Broderick; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1158-1169
A Theory of Label Propagation for Subpopulation Shift
Tianle Cai, Ruiqi Gao, Jason Lee, Qi Lei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1170-1182
Lenient Regret and Good-Action Identification in Gaussian Process Bandits
Xu Cai, Selwyn Gomes, Jonathan Scarlett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1183-1192
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
Hanqin Cai, Yuchen Lou, Daniel Mckenzie, Wotao Yin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1193-1203
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1204-1215
On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1216-1226
High-dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1227-1237
A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization
Andrew Campbell, Wenlong Chen, Vincent Stimper, Jose Miguel Hernandez-Lobato, Yichuan Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1238-1248
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris Holmes, Mert Gurbuzbalaban, Umut Simsekli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1249-1260
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design
Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1261-1271
Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1272-1282
Parameter-free Locally Accelerated Conditional Gradients
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1283-1293
Optimizing persistent homology based functions
Mathieu Carriere, Frederic Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1294-1303
Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with $\sqrt$T Regret
Asaf B Cassel, Tomer Koren; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1304-1313
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Multi-Receiver Online Bayesian Persuasion
Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1314-1323
Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data
Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1324-1335
Disentangling syntax and semantics in the brain with deep networks
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1336-1348
Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees
L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1349-1361
Best Model Identification: A Rested Bandit Formulation
Leonardo Cella, Massimiliano Pontil, Claudio Gentile; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1362-1372
Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research
Johan Samir Obando Ceron, Pablo Samuel Castro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1373-1383
Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1384-1394
Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks
Ciwan Ceylan, Salla Franzén, Florian T. Pokorny; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1395-1406
GRAND: Graph Neural Diffusion
Ben Chamberlain, James Rowbottom, Maria I Gorinova, Michael Bronstein, Stefan Webb, Emanuele Rossi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1407-1418
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
Ines Chami, Albert Gu, Dat P Nguyen, Christopher Re; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1419-1429
Goal-Conditioned Reinforcement Learning with Imagined Subgoals
Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1430-1440
Locally Private k-Means in One Round
Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1441-1451
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Tom Griffiths; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1452-1462
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, Jose M Alvarez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1463-1472
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DeepWalking Backwards: From Embeddings Back to Graphs
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos Tsourakakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1473-1483
Differentiable Spatial Planning using Transformers
Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1484-1495
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Henry J Charlesworth, Giovanni Montana; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1496-1506
Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1507-1517
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1518-1528
Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1529-1538
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Unsupervised Learning of Visual 3D Keypoints for Control
Boyuan Chen, Pieter Abbeel, Deepak Pathak; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1539-1549
Integer Programming for Causal Structure Learning in the Presence of Latent Variables
Rui Chen, Sanjeeb Dash, Tian Gao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1550-1560
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1561-1570
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1571-1581
Neural Feature Matching in Implicit 3D Representations
Yunlu Chen, Basura Fernando, Hakan Bilen, Thomas Mensink, Efstratios Gavves; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1582-1593
Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1594-1605
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1606-1616
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Mandoline: Model Evaluation under Distribution Shift
Mayee Chen, Karan Goel, Nimit S Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Re; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1617-1629
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco Ruiz, Liping Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1630-1639
CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang, Li Yinli, Cong Wang, Chao Shen, Qi Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1640-1650
Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case
Liyu Chen, Haipeng Luo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1651-1660
SpreadsheetCoder: Formula Prediction from Semi-structured Context
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1661-1672
Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1673-1683
Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Yuzhou Chen, Ignacio Segovia, Yulia R. Gel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1684-1694
A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1695-1706
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1707-1716
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps
Renyi Chen, Molei Tao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1717-1727
Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, Shashanka Ubaru; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1728-1739
Large-Scale Multi-Agent Deep FBSDEs
Tianrong Chen, Ziyi O Wang, Ioannis Exarchos, Evangelos Theodorou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1740-1748
Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1749-1759
Overcoming Catastrophic Forgetting by Bayesian Generative Regularization
Pei-Hung Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1760-1770
Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1771-1780
A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1781-1790
Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1791-1802
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph Gonzalez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1803-1813
SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
Wuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1814-1824
Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
Yong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1825-1835
Exact Optimization of Conformal Predictors via Incremental and Decremental Learning
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1836-1845
Problem Dependent View on Structured Thresholding Bandit Problems
James Cheshire, Pierre Menard, Alexandra Carpentier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1846-1854
Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
Yun Kuen Cheung, Georgios Piliouras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1855-1865
Understanding and Mitigating Accuracy Disparity in Regression
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1866-1876
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1877-1887
Light RUMs
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1888-1897
Parallelizing Legendre Memory Unit Training
Narsimha Reddy Chilkuri, Chris Eliasmith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1898-1907
Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies
Uthsav Chitra, Kimberly Ding, Jasper C.H. Lee, Benjamin J Raphael; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1908-1919
Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Tomasz Żołna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1920-1930
Unifying Vision-and-Language Tasks via Text Generation
Jaemin Cho, Jie Lei, Hao Tan, Mohit Bansal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1931-1942
Learning from Nested Data with Ornstein Auto-Encoders
Youngwon Choi, Sungdong Lee, Joong-Ho Won; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1943-1952
Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1953-1963
Label-Only Membership Inference Attacks
Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1964-1974
Modeling Hierarchical Structures with Continuous Recursive Neural Networks
Jishnu Ray Chowdhury, Cornelia Caragea; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1975-1988
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Muhammad A Rahman, Stefano V Albrecht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1989-1998
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Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wesley Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:1999-2009
First-Order Methods for Wasserstein Distributionally Robust MDP
Julien Grand Clement, Christian Kroer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2010-2019
Phasic Policy Gradient
Karl W Cobbe, Jacob Hilton, Oleg Klimov, John Schulman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2020-2027
Riemannian Convex Potential Maps
Samuel Cohen, Brandon Amos, Yaron Lipman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2028-2038
Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier, Renyuan Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2039-2048
Differentially-Private Clustering of Easy Instances
Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2049-2059
Improving Ultrametrics Embeddings Through Coresets
Vincent Cohen-Addad, Rémi De Joannis De Verclos, Guillaume Lagarde; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2060-2068
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Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2069-2078
Concentric mixtures of Mallows models for top-$k$ rankings: sampling and identifiability
Fabien Collas, Ekhine Irurozki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2079-2088
Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2089-2099
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2100-2111
Fairness and Bias in Online Selection
Jose Correa, Andres Cristi, Paul Duetting, Ashkan Norouzi-Fard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2112-2121
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Relative Deviation Margin Bounds
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2122-2131
A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2132-2143
Characterizing Fairness Over the Set of Good Models Under Selective Labels
Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2144-2155
Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering
Romain Couillet, Florent Chatelain, Nicolas Le Bihan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2156-2165
Explaining Time Series Predictions with Dynamic Masks
Jonathan Crabbé, Mihaela Van Der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2166-2177
Generalised Lipschitz Regularisation Equals Distributional Robustness
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2178-2188
Environment Inference for Invariant Learning
Elliot Creager, Joern-Henrik Jacobsen, Richard Zemel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2189-2200
Mind the Box: $l_1$-APGD for Sparse Adversarial Attacks on Image Classifiers
Francesco Croce, Matthias Hein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2201-2211
Parameterless Transductive Feature Re-representation for Few-Shot Learning
Wentao Cui, Yuhong Guo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2212-2221
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Randomized Algorithms for Submodular Function Maximization with a $k$-System Constraint
Shuang Cui, Kai Han, Tianshuai Zhu, Jing Tang, Benwei Wu, He Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2222-2232
GBHT: Gradient Boosting Histogram Transform for Density Estimation
Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2233-2243
ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations
Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F P O’Boyle, Hugh Leather; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2244-2253
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2254-2264
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
Mihaela Curmei, Sarah Dean, Benjamin Recht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2265-2275
Dynamic Balancing for Model Selection in Bandits and RL
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2276-2285
ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
Stéphane D’Ascoli, Hugo Touvron, Matthew L Leavitt, Ari S Morcos, Giulio Biroli, Levent Sagun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2286-2296
Consistent regression when oblivious outliers overwhelm
Tommaso D’Orsi, Gleb Novikov, David Steurer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2297-2306
Offline Reinforcement Learning with Pseudometric Learning
Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2307-2318
A Tale of Two Efficient and Informative Negative Sampling Distributions
Shabnam Daghaghi, Tharun Medini, Nicholas Meisburger, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2319-2329
SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Purushottam Kar, Manik Varma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2330-2340
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Fixed-Parameter and Approximation Algorithms for PCA with Outliers
Yogesh Dahiya, Fedor Fomin, Fahad Panolan, Kirill Simonov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2341-2351
Sliced Iterative Normalizing Flows
Biwei Dai, Uros Seljak; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2352-2364
Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D’Eramo, Jan Peters, Joni Pajarinen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2365-2375
Demonstration-Conditioned Reinforcement Learning for Few-Shot Imitation
Christopher R. Dance, Julien Perez, Théo Cachet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2376-2387
Re-understanding Finite-State Representations of Recurrent Policy Networks
Mohamad H Danesh, Anurag Koul, Alan Fern, Saeed Khorram; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2388-2397
Newton Method over Networks is Fast up to the Statistical Precision
Amir Daneshmand, Gesualdo Scutari, Pavel Dvurechensky, Alexander Gasnikov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2398-2409
BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders
Dominic Danks, Christopher Yau; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2410-2420
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2421-2432
Measuring Robustness in Deep Learning Based Compressive Sensing
Mohammad Zalbagi Darestani, Akshay S Chaudhari, Reinhard Heckel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2433-2444
SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Chandra Das, Myounggyu Won; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2445-2455
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Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2456-2466
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Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers
Jyotikrishna Dass, Rabi Mahapatra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2467-2477
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
Deepesh Data, Suhas Diggavi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2478-2488
Catformer: Designing Stable Transformers via Sensitivity Analysis
Jared Q Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Re, Chelsea Finn, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2489-2499
Diffusion Source Identification on Networks with Statistical Confidence
Quinlan E Dawkins, Tianxi Li, Haifeng Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2500-2509
Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James U Allingham, Javier Antoran, Jose Miguel Hernandez-Lobato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2510-2521
Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak Kiani, Seth Lloyd; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2522-2534
High-Dimensional Gaussian Process Inference with Derivatives
Filip de Roos, Alexandra Gessner, Philipp Hennig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2535-2545
Transfer-Based Semantic Anomaly Detection
Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2546-2558
Grid-Functioned Neural Networks
Javier Dehesa, Andrew Vidler, Julian Padget, Christof Lutteroth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2559-2567
Multidimensional Scaling: Approximation and Complexity
Erik Demaine, Adam Hesterberg, Frederic Koehler, Jayson Lynch, John Urschel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2568-2578
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng, Stephen Gould, Liang Zheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2579-2589
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Toward Better Generalization Bounds with Locally Elastic Stability
Zhun Deng, Hangfeng He, Weijie Su; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2590-2600
Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing
Yuan Deng, Sebastien Lahaie, Vahab Mirrokni, Song Zuo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2601-2610
Heterogeneity for the Win: One-Shot Federated Clustering
Don Kurian Dennis, Tian Li, Virginia Smith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2611-2620
Kernel Continual Learning
Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees Snoek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2621-2631
Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2632-2643
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2644-2653
Versatile Verification of Tree Ensembles
Laurens Devos, Wannes Meert, Jesse Davis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2654-2664
On the Inherent Regularization Effects of Noise Injection During Training
Oussama Dhifallah, Yue Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2665-2675
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirrokni, Jessica Shi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2676-2686
Learning Online Algorithms with Distributional Advice
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Ali Vakilian, Nikos Zarifis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2687-2696
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A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2697-2706
Context-Aware Online Collective Inference for Templated Graphical Models
Charles Dickens, Connor Pryor, Eriq Augustine, Alexander Miller, Lise Getoor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2707-2716
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ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables
Aleksandar Dimitriev, Mingyuan Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2717-2727
XOR-CD: Linearly Convergent Constrained Structure Generation
Fan Ding, Jianzhu Ma, Jinbo Xu, Yexiang Xue; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2728-2738
Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
Tianyu Ding, Zhihui Zhu, Rene Vidal, Daniel P Robinson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2739-2748
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Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2749-2759
Estimation and Quantization of Expected Persistence Diagrams
Vincent Divol, Theo Lacombe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2760-2770
On Energy-Based Models with Overparametrized Shallow Neural Networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2771-2782
Kernel-Based Reinforcement Learning: A Finite-Time Analysis
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2783-2792
Attention is not all you need: pure attention loses rank doubly exponentially with depth
Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2793-2803
How rotational invariance of common kernels prevents generalization in high dimensions
Konstantin Donhauser, Mingqi Wu, Fanny Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2804-2814
Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction
Radu Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2815-2825
Bilinear Classes: A Structural Framework for Provable Generalization in RL
Simon Du, Sham Kakade, Jason Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2826-2836
Improved Contrastive Divergence Training of Energy-Based Models
Yilun Du, Shuang Li, Joshua Tenenbaum, Igor Mordatch; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2837-2848
Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
Cunxiao Du, Zhaopeng Tu, Jing Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2849-2859
Putting the “Learning" into Learning-Augmented Algorithms for Frequency Estimation
Elbert Du, Franklyn Wang, Michael Mitzenmacher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2860-2869
Estimating $α$-Rank from A Few Entries with Low Rank Matrix Completion
Yali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2870-2879
Learning Diverse-Structured Networks for Adversarial Robustness
Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2880-2891
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2892-2902
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network
Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2903-2913
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Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics
Arkopal Dutt, Andrey Lokhov, Marc D Vuffray, Sidhant Misra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2914-2925
Reinforcement Learning Under Moral Uncertainty
Adrien Ecoffet, Joel Lehman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2926-2936
Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2937-2947
Self-Paced Context Evaluation for Contextual Reinforcement Learning
Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2948-2958
Provably Strict Generalisation Benefit for Equivariant Models
Bryn Elesedy, Sheheryar Zaidi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2959-2969
Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2970-2981
Implicit Bias of Linear RNNs
Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K Fletcher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2982-2992
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
Tolga Ergen, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2993-3003
Revealing the Structure of Deep Neural Networks via Convex Duality
Tolga Ergen, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3004-3014
Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, Nicu Sebe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3015-3024
Graph Mixture Density Networks
Federico Errica, Davide Bacciu, Alessio Micheli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3025-3035
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Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data
Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3036-3046
Weight-covariance alignment for adversarially robust neural networks
Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy Hospedales; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3047-3056
Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3057-3067
Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks
Xuhui Fan, Bin Li, Yaqiong Li, Scott A. Sisson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3068-3077
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling
Ying Fan, Yifei Ming; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3078-3087
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Animashree Anandkumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3088-3099
On Estimation in Latent Variable Models
Guanhua Fang, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3100-3110
On Variational Inference in Biclustering Models
Guanhua Fang, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3111-3121
Learning Bounds for Open-Set Learning
Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3122-3132
Streaming Bayesian Deep Tensor Factorization
Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3133-3142
PID Accelerated Value Iteration Algorithm
Amir-Massoud Farahmand, Mohammad Ghavamzadeh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3143-3153
Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew A Li, Tianyi Peng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3154-3163
Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results
Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3164-3173
Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3174-3185
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation
Kilian Fatras, Thibault Sejourne, Rémi Flamary, Nicolas Courty; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3186-3197
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach
Yingjie Fei, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3198-3207
Lossless Compression of Efficient Private Local Randomizers
Vitaly Feldman, Kunal Talwar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3208-3219
Dimensionality Reduction for the Sum-of-Distances Metric
Zhili Feng, Praneeth Kacham, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3220-3229
Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sebastien Lahaie, Jon Schneider, Jinchao Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3230-3239
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Uncertainty Principles of Encoding GANs
Ruili Feng, Zhouchen Lin, Jiapeng Zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3240-3251
Pointwise Binary Classification with Pairwise Confidence Comparisons
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3252-3262
Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3263-3273
KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
Haozhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3274-3283
Understanding Noise Injection in GANs
Ruili Feng, Deli Zhao, Zheng-Jun Zha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3284-3293
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
Matthias Fey, Jan E. Lenssen, Frank Weichert, Jure Leskovec; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3294-3304
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning
Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3305-3317
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Marc Finzi, Max Welling, Andrew Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3318-3328
Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Dr.Regina Barzilay; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3329-3339
Scalable Certified Segmentation via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3340-3351
What’s in the Box? Exploring the Inner Life of Neural Networks with Robust Rules
Jonas Fischer, Anna Olah, Jilles Vreeken; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3352-3362
Online Learning with Optimism and Delay
Genevieve E Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3363-3373
Online A-Optimal Design and Active Linear Regression
Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3374-3383
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi R Ivanova, Ilyas Malik, Tom Rainforth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3384-3395
Efficient Online Learning for Dynamic k-Clustering
Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3396-3406
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3407-3416
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3417-3426
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3427-3438
Post-selection inference with HSIC-Lasso
Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3439-3448
Variational Data Assimilation with a Learned Inverse Observation Operator
Thomas Frerix, Dmitrii Kochkov, Jamie Smith, Daniel Cremers, Michael Brenner, Stephan Hoyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3449-3458
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Bayesian Quadrature on Riemannian Data Manifolds
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3459-3468
Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing
Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3469-3479
Learning Task Informed Abstractions
Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi Jaakkola; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3480-3491
Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference
Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3492-3504
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3505-3517
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
Scott Fujimoto, David Meger, Doina Precup; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3518-3529
Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3530-3540
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3541-3552
An Information-Geometric Distance on the Space of Tasks
Yansong Gao, Pratik Chaudhari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3553-3563
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks
Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3564-3575
Unsupervised Co-part Segmentation through Assembly
Qingzhe Gao, Bin Wang, Libin Liu, Baoquan Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3576-3586
Discriminative Complementary-Label Learning with Weighted Loss
Yi Gao, Min-Ling Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3587-3597
RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3598-3609
On Proximal Policy Optimization’s Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3610-3619
What does LIME really see in images?
Damien Garreau, Dina Mardaoui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3620-3629
Parametric Graph for Unimodal Ranking Bandit
Camille-Sovanneary Gauthier, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3630-3639
Let’s Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework
Floris Geerts, Filip Mazowiecki, Guillermo Perez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3640-3649
On the difficulty of unbiased alpha divergence minimization
Tomas Geffner, Justin Domke; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3650-3659
How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference
Amanda M Gentzel, Purva Pruthi, David Jensen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3660-3671
Strategic Classification in the Dark
Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3672-3681
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3682-3691
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3692-3701
The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, Viswanath Nagarajan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3702-3712
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Differentially Private Quantiles
Jennifer Gillenwater, Matthew Joseph, Alex Kulesza; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3713-3722
Query Complexity of Adversarial Attacks
Grzegorz Gluch, Rüdiger Urbanke; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3723-3733
Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective
Florin Gogianu, Tudor Berariu, Mihaela C Rosca, Claudia Clopath, Lucian Busoniu, Razvan Pascanu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3734-3744
12-Lead ECG Reconstruction via Koopman Operators
Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3745-3754
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Function Contrastive Learning of Transferable Meta-Representations
Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3755-3765
Active Slices for Sliced Stein Discrepancy
Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jose Miguel Hernandez-Lobato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3766-3776
On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3777-3787
MARINA: Faster Non-Convex Distributed Learning with Compression
Eduard Gorbunov, Konstantin P. Burlachenko, Zhize Li, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3788-3798
Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures
Martijn M Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3799-3808
Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3809-3820
Dissecting Supervised Contrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3821-3830
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris Maddison; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3831-3841
Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg, Shie Mannor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3842-3853
Crystallization Learning with the Delaunay Triangulation
Jiaqi Gu, Guosheng Yin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3854-3863
AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, Wenwu Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3864-3874
Operationalizing Complex Causes: A Pragmatic View of Mediation
Limor Gultchin, David Watson, Matt Kusner, Ricardo Silva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3875-3885
On a Combination of Alternating Minimization and Nesterov’s Momentum
Sergey Guminov, Pavel Dvurechensky, Nazarii Tupitsa, Alexander Gasnikov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3886-3898
Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games
Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3899-3909
Adversarial Policy Learning in Two-player Competitive Games
Wenbo Guo, Xian Wu, Sui Huang, Xinyu Xing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3910-3919
Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3920-3929
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3930-3941
Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting
Chirag Gupta, Aaditya Ramdas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3942-3952
Correcting Exposure Bias for Link Recommendation
Shantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3953-3963
The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3964-3975
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3976-3987
Adapting to Delays and Data in Adversarial Multi-Armed Bandits
Andras Gyorgy, Pooria Joulani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3988-3997
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:3998-4007
Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach
Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4008-4017
Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
Seungyul Han, Youngchul Sung; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4018-4029
Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4030-4039
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A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
Mengyue Hang, Jennifer Neville, Bruno Ribeiro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4040-4050
Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning
Austin W. Hanjie, Victor Y Zhong, Karthik Narasimhan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4051-4062
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4063-4073
Bootstrapping Fitted Q-Evaluation for Off-Policy Inference
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4074-4084
Compressed Maximum Likelihood
Yi Hao, Alon Orlitsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4085-4095
Valid Causal Inference with (Some) Invalid Instruments
Jason S Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4096-4106
Model Performance Scaling with Multiple Data Sources
Tatsunori Hashimoto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4107-4116
Hierarchical VAEs Know What They Don’t Know
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4117-4128
SPECTRE: defending against backdoor attacks using robust statistics
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4129-4139
Boosting for Online Convex Optimization
Elad Hazan, Karan Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4140-4149
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PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4150-4159
SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw Waveform
Yuhang He, Niki Trigoni, Andrew Markham; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4160-4170
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Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4171-4180
Finding Relevant Information via a Discrete Fourier Expansion
Mohsen Heidari, Jithin Sreedharan, Gil I Shamir, Wojciech Szpankowski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4181-4191
Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging
Amélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4192-4202
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
Ryan Henderson, Djork-Arné Clevert, Floriane Montanari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4203-4213
Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado Van Hasselt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4214-4226
Learning Representations by Humans, for Humans
Sophie Hilgard, Nir Rosenfeld, Mahzarin R Banaji, Jack Cao, David Parkes; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4227-4238
Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4239-4249
Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4250-4261
Multiplicative Noise and Heavy Tails in Stochastic Optimization
Liam Hodgkinson, Michael Mahoney; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4262-4274
MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey S Nearing, Sepp Hochreiter, Guenter Klambauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4275-4286
Learning Curves for Analysis of Deep Networks
Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal Shlapentokh-Rothman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4287-4296
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes
Peter Holderrieth, Michael J Hutchinson, Yee Whye Teh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4297-4307
Latent Programmer: Discrete Latent Codes for Program Synthesis
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4308-4318
Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Taehyun Cho, Jungwoo Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4319-4327
Federated Learning of User Verification Models Without Sharing Embeddings
Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4328-4336
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The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4337-4348
Near-Optimal Representation Learning for Linear Bandits and Linear RL
Jiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4349-4358
On the Random Conjugate Kernel and Neural Tangent Kernel
Zhengmian Hu, Heng Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4359-4368
Off-Belief Learning
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, Jakob Foerster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4369-4379
Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4380-4390
A Scalable Deterministic Global Optimization Algorithm for Clustering Problems
Kaixun Hua, Mingfei Shi, Yankai Cao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4391-4401
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On Recovering from Modeling Errors Using Testing Bayesian Networks
Haiying Huang, Adnan Darwiche; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4402-4411
A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, Wenjie Liu, Nikolaos Freris, Hu Ding; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4412-4422
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FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4423-4434
STRODE: Stochastic Boundary Ordinary Differential Equation
Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4435-4445
A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance
Minhui Huang, Shiqian Ma, Lifeng Lai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4446-4455
Projection Robust Wasserstein Barycenters
Minhui Huang, Shiqian Ma, Lifeng Lai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4456-4465
Accurate Post Training Quantization With Small Calibration Sets
Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4466-4475
Learning and Planning in Complex Action Spaces
Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4476-4486
Generative Adversarial Transformers
Drew A Hudson, Larry Zitnick; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4487-4499
Neural Pharmacodynamic State Space Modeling
Zeshan M Hussain, Rahul G. Krishnan, David Sontag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4500-4510
Hyperparameter Selection for Imitation Learning
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4511-4522
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Jason Chiang, Vyas Sekar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4523-4532
LieTransformer: Equivariant Self-Attention for Lie Groups
Michael J Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4533-4543
Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization
Shahana Ibrahim, Xiao Fu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4544-4554
Selecting Data Augmentation for Simulating Interventions
Maximilian Ilse, Jakub M Tomczak, Patrick Forré; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4555-4562
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Khan Mohammad Emtiyaz; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4563-4573
Active Learning for Distributionally Robust Level-Set Estimation
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4574-4584
Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4585-4595
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian A Schroeder De Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4596-4606
Randomized Exploration in Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4607-4616
Distributed Second Order Methods with Fast Rates and Compressed Communication
Rustem Islamov, Xun Qian, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4617-4628
What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov, Sharad Vikram, Matthew D Hoffman, Andrew Gordon Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4629-4640
How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4641-4650
Perceiver: General Perception with Iterative Attention
Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, Joao Carreira; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4651-4664
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Imitation by Predicting Observations
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4665-4676
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Local Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4677-4686
Alternative Microfoundations for Strategic Classification
Meena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4687-4697
Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4698-4708
Instance-Optimal Compressed Sensing via Posterior Sampling
Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4709-4720
Fairness for Image Generation with Uncertain Sensitive Attributes
Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4721-4732
Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4733-4743
Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4744-4754
Inverse Decision Modeling: Learning Interpretable Representations of Behavior
Daniel Jarrett, Alihan Hüyük, Mihaela Van Der Schaar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4755-4771
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo B Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4772-4784
Policy Gradient Bayesian Robust Optimization for Imitation Learning
Zaynah Javed, Daniel S Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca Dragan, Ken Goldberg; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4785-4796
In-Database Regression in Input Sparsity Time
Rajesh Jayaram, Alireza Samadian, David Woodruff, Peng Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4797-4806
Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4807-4818
Objective Bound Conditional Gaussian Process for Bayesian Optimization
Taewon Jeong, Heeyoung Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4819-4828
Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
Andrew Jesson, Sören Mindermann, Yarin Gal, Uri Shalit; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4829-4838
DeepReDuce: ReLU Reduction for Fast Private Inference
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4839-4849
Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction
Aditi Jha, Michael J. Morais, Jonathan W Pillow; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4850-4859
Fast margin maximization via dual acceleration
Ziwei Ji, Nathan Srebro, Matus Telgarsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4860-4869
Marginalized Stochastic Natural Gradients for Black-Box Variational Inference
Geng Ji, Debora Sujono, Erik B Sudderth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4870-4881
Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4882-4892
Efficient Statistical Tests: A Neural Tangent Kernel Approach
Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4893-4903
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4904-4916
Multi-Dimensional Classification via Sparse Label Encoding
Bin-Bin Jia, Min-Ling Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4917-4926
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Self-Damaging Contrastive Learning
Ziyu Jiang, Tianlong Chen, Bobak J Mortazavi, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4927-4939
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Prioritized Level Replay
Minqi Jiang, Edward Grefenstette, Tim Rocktäschel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4940-4950
Monotonic Robust Policy Optimization with Model Discrepancy
Yuankun Jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4951-4960
Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4961-4970
Streaming and Distributed Algorithms for Robust Column Subset Selection
Shuli Jiang, Dennis Li, Irene Mengze Li, Arvind V Mahankali, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4971-4981
Single Pass Entrywise-Transformed Low Rank Approximation
Yifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4982-4991
The Emergence of Individuality
Jiechuan Jiang, Zongqing Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:4992-5001
Online Selection Problems against Constrained Adversary
Zhihao Jiang, Pinyan Lu, Zhihao Gavin Tang, Yuhao Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5002-5012
Active Covering
Heinrich Jiang, Afshin Rostamizadeh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5013-5022
Emphatic Algorithms for Deep Reinforcement Learning
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado Van Hasselt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5023-5033
Characterizing Structural Regularities of Labeled Data in Overparameterized Models
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C Mozer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5034-5044
Optimal Streaming Algorithms for Multi-Armed Bandits
Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5045-5054
Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
Yujia Jin, Aaron Sidford; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5055-5064
Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5065-5073
MOTS: Minimax Optimal Thompson Sampling
Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5074-5083
Is Pessimism Provably Efficient for Offline RL?
Ying Jin, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5084-5096
Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5097-5106
Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
Changhun Jo, Kangwook Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5107-5117
Provable Lipschitz Certification for Generative Models
Matt Jordan, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5118-5126
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data
Martin Jørgensen, Soren Hauberg; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5127-5136
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On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models
Peizhong Ju, Xiaojun Lin, Ness Shroff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5137-5147
Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5148-5157
Detection of Signal in the Spiked Rectangular Models
Ji Hyung Jung, Hye Won Chung, Ji Oon Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5158-5167
Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning
Yonghan Jung, Jin Tian, Elias Bareinboim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5168-5179
A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel P Robinson, Enrique Mallada, Rene Vidal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5180-5188
Training Recurrent Neural Networks via Forward Propagation Through Time
Anil Kag, Venkatesh Saligrama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5189-5200
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation
Peter Kairouz, Ziyu Liu, Thomas Steinke; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5201-5212
Practical and Private (Deep) Learning Without Sampling or Shuffling
Peter Kairouz, Brendan Mcmahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5213-5225
A Differentiable Point Process with Its Application to Spiking Neural Networks
Hiroshi Kajino; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5226-5235
Projection techniques to update the truncated SVD of evolving matrices with applications
Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth Clarkson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5236-5246
Optimal Off-Policy Evaluation from Multiple Logging Policies
Nathan Kallus, Yuta Saito, Masatoshi Uehara; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5247-5256
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5257-5268
Statistical Estimation from Dependent Data
Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5269-5278
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes
Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Gordon Wilson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5279-5289
Variational Auto-Regressive Gaussian Processes for Continual Learning
Sanyam Kapoor, Theofanis Karaletsos, Thang D Bui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5290-5300
Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5301-5310
Learning from History for Byzantine Robust Optimization
Sai Praneeth Karimireddy, Lie He, Martin Jaggi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5311-5319
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
Masahiro Kato, Takeshi Teshima; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5320-5333
Improved Algorithms for Agnostic Pool-based Active Classification
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5334-5344
When Does Data Augmentation Help With Membership Inference Attacks?
Yigitcan Kaya, Tudor Dumitras; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5345-5355
Regularized Submodular Maximization at Scale
Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5356-5366
Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A Kelkar, Mark Anastasio; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5367-5377
Self Normalizing Flows
Thomas A Keller, Jorn W.T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5378-5387
Interpretable Stability Bounds for Spectral Graph Filters
Henry Kenlay, Dorina Thanou, Xiaowen Dong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5388-5397
Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets
Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5398-5408
Markpainting: Adversarial Machine Learning meets Inpainting
David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross Anderson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5409-5419
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5420-5431
Functional Space Analysis of Local GAN Convergence
Valentin Khrulkov, Artem Babenko, Ivan Oseledets; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5432-5442
"Hey, that’s not an ODE": Faster ODE Adjoints via Seminorms
Patrick Kidger, Ricky T. Q. Chen, Terry J Lyons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5443-5452
Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry J Lyons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5453-5463
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
Krishnateja Killamsetty, Durga S, Ganesh Ramakrishnan, Abir De, Rishabh Iyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5464-5474
Improving Predictors via Combination Across Diverse Task Categories
Kwang In Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5475-5485
Self-Improved Retrosynthetic Planning
Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5486-5495
Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5496-5505
I-BERT: Integer-only BERT Quantization
Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5506-5518
Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph J Lim, Byoung-Tak Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5519-5529
Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
Jaehyeon Kim, Jungil Kong, Juhee Son; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5530-5540
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong Ki Kim, Miao Liu, Matthew D Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan How; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5541-5550
Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations
Timothy D. Kim, Thomas Z. Luo, Jonathan W. Pillow, Carlos D. Brody; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5551-5561
The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5562-5571
Unsupervised Skill Discovery with Bottleneck Option Learning
Jaekyeom Kim, Seohong Park, Gunhee Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5572-5582
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
Wonjae Kim, Bokyung Son, Ildoo Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5583-5594
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Bias-Robust Bayesian Optimization via Dueling Bandits
Johannes Kirschner, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5595-5605
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CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients
Dani Kiyasseh, Tingting Zhu, David A Clifton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5606-5615
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Gasteiger, Marten Lienen, Stephan Günnemann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5616-5627
Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5628-5636
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara M Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5637-5664
One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5665-5675
A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5676-5685
Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5686-5696
A Distribution-dependent Analysis of Meta Learning
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5697-5706
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5707-5718
Kernel Stein Discrepancy Descent
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5719-5730
Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5731-5741
NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam R Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo Jimenez Rezende; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5742-5752
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Active Testing: Sample-Efficient Model Evaluation
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5753-5763
High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott M Jordan, Georgios Theocharous, Philip Thomas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5764-5773
Offline Reinforcement Learning with Fisher Divergence Critic Regularization
Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5774-5783
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
Dmitry Kovalev, Egor Shulgin, Peter Richtarik, Alexander V Rogozin, Alexander Gasnikov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5784-5793
Revisiting Peng’s Q($λ$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5794-5804
Adapting to misspecification in contextual bandits with offline regression oracles
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5805-5814
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Joern-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5815-5826
Near-Optimal Confidence Sequences for Bounded Random Variables
Arun K Kuchibhotla, Qinqing Zheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5827-5837
Differentially Private Bayesian Inference for Generalized Linear Models
Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5838-5849
Bayesian Structural Adaptation for Continual Learning
Abhishek Kumar, Sunabha Chatterjee, Piyush Rai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5850-5860
Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5861-5871
A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
Christian Kümmerle, Claudio M. Verdun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5872-5883
Meta-Thompson Sampling
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5884-5893
Targeted Data Acquisition for Evolving Negotiation Agents
Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5894-5904
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5905-5914
On the price of explainability for some clustering problems
Eduardo S Laber, Lucas Murtinho; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5915-5925
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5926-5936
Generalization Bounds in the Presence of Outliers: a Median-of-Means Study
Pierre Laforgue, Guillaume Staerman, Stephan Clémençon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5937-5947
Model Fusion for Personalized Learning
Thanh Chi Lam, Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5948-5958
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5959-5968
Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5969-5978
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Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela, Brenden K Petersen, Sookyung Kim, Claudio P Santiago, Ruben Glatt, Nathan Mundhenk, Jacob F Pettit, Daniel Faissol; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5979-5989
Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch)
Hunter Lang, David Sontag, Aravindan Vijayaraghavan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:5990-5999
Efficient Message Passing for 0–1 ILPs with Binary Decision Diagrams
Jan-Hendrik Lange, Paul Swoboda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6000-6010
CountSketches, Feature Hashing and the Median of Three
Kasper Green Larsen, Rasmus Pagh, Jakub Tětek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6011-6020
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MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie C. Laturnus, Philipp Berens; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6021-6031
Improved Regret Bound and Experience Replay in Regularized Policy Iteration
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6032-6042
LAMDA: Label Matching Deep Domain Adaptation
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6043-6054
Gaussian Process-Based Real-Time Learning for Safety Critical Applications
Armin Lederer, Alejandro J Ordóñez Conejo, Korbinian A Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6055-6064
Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6065-6075
Fair Selective Classification Via Sufficiency
Joshua K Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W Wornell; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6076-6086
On-the-fly Rectification for Robust Large-Vocabulary Topic Inference
Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6087-6097
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
Dong Hoon Lee, Sae-Young Chung; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6098-6108
Continual Learning in the Teacher-Student Setup: Impact of Task Similarity
Sebastian Lee, Sebastian Goldt, Andrew Saxe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6109-6119
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byungjun Lee, Joelle Pineau, Kee-Eung Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6120-6130
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6131-6141
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6142-6151
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
Kimin Lee, Laura M Smith, Pieter Abbeel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6152-6163
Near-Optimal Linear Regression under Distribution Shift
Qi Lei, Wei Hu, Jason Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6164-6174
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6175-6186
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z Leibo, Edgar A Dueñez-Guzman, Alexander Vezhnevets, John P Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6187-6199
Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany J Vlaar, Timothée Pouchon, Amos Storkey; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6200-6211
Globally-Robust Neural Networks
Klas Leino, Zifan Wang, Matt Fredrikson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6212-6222
Learning to Price Against a Moving Target
Renato Paes Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6223-6232
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J Lyons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6233-6242
Strategic Classification Made Practical
Sagi Levanon, Nir Rosenfeld; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6243-6253
Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander J Levine, Soheil Feizi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6254-6264
BASE Layers: Simplifying Training of Large, Sparse Models
Mike Lewis, Shruti Bhosale, Tim Dettmers, Naman Goyal, Luke Zettlemoyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6265-6274
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Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models
Jose Lezama, Wei Chen, Qiang Qiu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6275-6285
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PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6286-6295
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6296-6306
Winograd Algorithm for AdderNet
Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6307-6315
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A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration
Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6316-6325
Privacy-Preserving Feature Selection with Secure Multiparty Computation
Xiling Li, Rafael Dowsley, Martine De Cock; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6326-6336
Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
Gen Li, Yuantao Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6337-6345
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MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H Pong, Aurick Zhou, Justin Yu, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6346-6356
Ditto: Fair and Robust Federated Learning Through Personalization
Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6357-6368
Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6369-6380
Approximate Group Fairness for Clustering
Bo Li, Lijun Li, Ankang Sun, Chenhao Wang, Yingfan Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6381-6391
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Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6392-6402
Provably End-to-end Label-noise Learning without Anchor Points
Xuefeng Li, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6403-6413
A Novel Method to Solve Neural Knapsack Problems
Duanshun Li, Jing Liu, Dongeun Lee, Ali Seyedmazloom, Giridhar Kaushik, Kookjin Lee, Noseong Park; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6414-6424
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Mixed Cross Entropy Loss for Neural Machine Translation
Haoran Li, Wei Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6425-6436
Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6437-6449
Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6450-6459
Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6460-6470
Testing DNN-based Autonomous Driving Systems under Critical Environmental Conditions
Zhong Li, Minxue Pan, Tian Zhang, Xuandong Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6471-6482
The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6483-6492
Distributionally Robust Optimization with Markovian Data
Mengmeng Li, Tobias Sutter, Daniel Kuhn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6493-6503
Communication-Efficient Distributed SVD via Local Power Iterations
Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6504-6514
FILTRA: Rethinking Steerable CNN by Filter Transform
Bo Li, Qili Wang, Gim Hee Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6515-6522
Online Unrelated Machine Load Balancing with Predictions Revisited
Shi Li, Jiayi Xian; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6523-6532
Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator
Zeng Li, Chuanlong Xie, Qinwen Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6533-6542
TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models
Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6543-6552
A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6553-6564
Towards Understanding and Mitigating Social Biases in Language Models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6565-6576
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability
Kaizhao Liang, Jacky Y Zhang, Boxin Wang, Zhuolin Yang, Sanmi Koyejo, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6577-6587
Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning
Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6588-6599
Information Obfuscation of Graph Neural Networks
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6600-6610
Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6611-6620
Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Q Davis, Adrian Weller; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6621-6630
Making transport more robust and interpretable by moving data through a small number of anchor points
Chi-Heng Lin, Mehdi Azabou, Eva Dyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6631-6641
Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation
Xiang Lin, Simeng Han, Shafiq Joty; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6642-6653
Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Sai Praneeth Karimireddy, Sebastian Stich, Martin Jaggi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6654-6665
Generative Causal Explanations for Graph Neural Networks
Wanyu Lin, Hao Lan, Baochun Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6666-6679
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Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Mohammad Emtiyaz, Mark Schmidt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6680-6691
Active Learning of Continuous-time Bayesian Networks through Interventions
Dominik Linzner, Heinz Koeppl; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6692-6701
Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6702-6712
The Earth Mover’s Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6713-6724
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments
Yang Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6725-6735
APS: Active Pretraining with Successor Features
Hao Liu, Pieter Abbeel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6736-6747
Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6748-6758
Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6759-6769
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6770-6780
Just Train Twice: Improving Group Robustness without Training Group Information
Evan Z Liu, Behzad Haghgoo, Annie S Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6781-6792
Event Outlier Detection in Continuous Time
Siqi Liu, Milos Hauskrecht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6793-6803
Heterogeneous Risk Minimization
Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6804-6814
Stochastic Iterative Graph Matching
Linfeng Liu, Michael C Hughes, Soha Hassoun, Liping Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6815-6825
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Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu, Unnat Jain, Raymond A Yeh, Alexander Schwing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6826-6836
Elastic Graph Neural Networks
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6837-6849
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One Pass Late Fusion Multi-view Clustering
Xinwang Liu, Li Liu, Qing Liao, Siwei Wang, Yi Zhang, Wenxuan Tu, Chang Tang, Jiyuan Liu, En Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6850-6859
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6860-6870
From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social Instruments
Yiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang, Bakhadyr Khoussainov, Liehuang Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6871-6881
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A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
Risheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6882-6892
Selfish Sparse RNN Training
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6893-6904
Temporal Difference Learning as Gradient Splitting
Rui Liu, Alex Olshevsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6905-6913
On Robust Mean Estimation under Coordinate-level Corruption
Zifan Liu, Jong Ho Park, Theodoros Rekatsinas, Christos Tzamos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6914-6924
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices
Evan Z Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6925-6935
How Do Adam and Training Strategies Help BNNs Optimization
Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6936-6946
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SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6947-6956
Learning Deep Neural Networks under Agnostic Corrupted Supervision
Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6957-6967
Leveraging Public Data for Practical Private Query Release
Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan Ullman, Steven Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6968-6977
Watermarking Deep Neural Networks with Greedy Residuals
Hanwen Liu, Zhenyu Weng, Yuesheng Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6978-6988
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Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:6989-7000
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7001-7010
Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7011-7020
Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7021-7032
Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7033-7044
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7045-7056
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7057-7066
Relative Positional Encoding for Transformers with Linear Complexity
Antoine Liutkus, Ondřej Cı́fka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gael Richard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7067-7079
Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos, Paul Grigas, Zheng Wen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7080-7089
Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7090-7101
HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture
Qian Lou, Lei Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7102-7110
Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7111-7123
DANCE: Enhancing saliency maps using decoys
Yang Young Lu, Wenbo Guo, Xinyu Xing, William Stafford Noble; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7124-7133
Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification
Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7134-7144
Variance Reduced Training with Stratified Sampling for Forecasting Models
Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7145-7155
ACE: Explaining cluster from an adversarial perspective
Yang Young Lu, Timothy C Yu, Giancarlo Bonora, William Stafford Noble; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7156-7167
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On Monotonic Linear Interpolation of Neural Network Parameters
James R Lucas, Juhan Bae, Michael R Zhang, Stanislav Fort, Richard Zemel, Roger B Grosse; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7168-7179
Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies.
Denis Lukovnikov, Asja Fischer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7180-7191
GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7192-7203
Trajectory Diversity for Zero-Shot Coordination
Andrei Lupu, Brandon Cui, Hengyuan Hu, Jakob Foerster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7204-7213
HyperHyperNetwork for the Design of Antenna Arrays
Shahar Lutati, Lior Wolf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7214-7223
Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7224-7234
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking
Xingchen Ma, Matthew B. Blaschko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7235-7245
Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface
Baorui Ma, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7246-7257
Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7258-7267
Local Algorithms for Finding Densely Connected Clusters
Peter Macgregor, He Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7268-7278
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Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7279-7289
Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason J Miller, Hongda Qiu, Ming Zhong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7290-7300
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7301-7312
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7313-7324
Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
Vien V. Mai, Mikael Johansson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7325-7335
Nonparametric Hamiltonian Monte Carlo
Carol Mak, Fabian Zaiser, Luke Ong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7336-7347
Exploiting structured data for learning contagious diseases under incomplete testing
Maggie Makar, Lauren West, David Hooper, Eric Horvitz, Erica Shenoy, John Guttag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7348-7357
Near-Optimal Algorithms for Explainable k-Medians and k-Means
Konstantin Makarychev, Liren Shan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7358-7367
KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok V Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7368-7378
Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7379-7389
Inverse Constrained Reinforcement Learning
Shehryar Malik, Usman Anwar, Alireza Aghasi, Ali Ahmed; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7390-7399
A Sampling-Based Method for Tensor Ring Decomposition
Osman Asif Malik, Stephen Becker; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7400-7411
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7412-7422
Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design
Gustavo Malkomes, Bolong Cheng, Eric H Lee, Mike Mccourt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7423-7434
Consistent Nonparametric Methods for Network Assisted Covariate Estimation
Xueyu Mao, Deepayan Chakrabarti, Purnamrita Sarkar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7435-7446
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Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7447-7458
Adaptive Sampling for Best Policy Identification in Markov Decision Processes
Aymen Al Marjani, Alexandre Proutiere; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7459-7468
Explanations for Monotonic Classifiers.
Joao Marques-Silva, Thomas Gerspacher, Martin C Cooper, Alexey Ignatiev, Nina Narodytska; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7469-7479
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Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7480-7491
Blind Pareto Fairness and Subgroup Robustness
Natalia L Martinez, Martin A Bertran, Afroditi Papadaki, Miguel Rodrigues, Guillermo Sapiro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7492-7501
Necessary and sufficient conditions for causal feature selection in time series with latent common causes
Atalanti A Mastakouri, Bernhard Schölkopf, Dominik Janzing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7502-7511
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt Kusner, Arthur Gretton, Krikamol Muandet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7512-7523
Robust Unsupervised Learning via L-statistic Minimization
Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7524-7533
Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H Bach, Eli Upfal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7534-7543
Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7544-7554
Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7555-7564
Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7565-7577
A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions
Gabriel Mel, Surya Ganguli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7578-7587
Neural Architecture Search without Training
Joe Mellor, Jack Turner, Amos Storkey, Elliot J Crowley; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7588-7598
Fast active learning for pure exploration in reinforcement learning
Pierre Menard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7599-7608
UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre Menard, Omar Darwiche Domingues, Xuedong Shang, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7609-7618
An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7619-7631
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A statistical perspective on distillation
Aditya K Menon, Ankit Singh Rawat, Sashank Reddi, Seungyeon Kim, Sanjiv Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7632-7642
Learn2Hop: Learned Optimization on Rough Landscapes
Amil Merchant, Luke Metz, Samuel S Schoenholz, Ekin D Cubuk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7643-7653
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7654-7664
Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7665-7676
Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael B Pinot, Jamal Atif, Yann Chevaleyre; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7677-7687
Learning in Nonzero-Sum Stochastic Games with Potentials
David H Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, Minne Li, Ying Wen, Joel Jennings, Jun Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7688-7699
EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture
Chenfeng Miao, Liang Shuang, Zhengchen Liu, Chen Minchuan, Jun Ma, Shaojun Wang, Jing Xiao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7700-7709
Outside the Echo Chamber: Optimizing the Performative Risk
John P Miller, Juan C Perdomo, Tijana Zrnic; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7710-7720
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John P Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7721-7735
Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7736-7747
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
Dongchan Min, Dong Bok Lee, Eunho Yang, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7748-7759
On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7760-7768
An Identifiable Double VAE For Disentangled Representations
Graziano Mita, Maurizio Filippone, Pietro Michiardi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7769-7779
Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7780-7791
The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori F Ebihara; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7792-7804
PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7805-7817
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
Dustin Morrill, Ryan D’Orazio, Marc Lanctot, James R Wright, Michael Bowling, Amy R Greenwald; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7818-7828
Neural Rough Differential Equations for Long Time Series
James Morrill, Cristopher Salvi, Patrick Kidger, James Foster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7829-7838
Connecting Interpretability and Robustness in Decision Trees through Separation
Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7839-7849
Outlier-Robust Optimal Transport
Debarghya Mukherjee, Aritra Guha, Justin M Solomon, Yuekai Sun, Mikhail Yurochkin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7850-7860
Oblivious Sketching for Logistic Regression
Alexander Munteanu, Simon Omlor, David Woodruff; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7861-7871
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
Tomoya Murata, Taiji Suzuki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7872-7881
Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
Kieran A Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7882-7893
No-regret Algorithms for Capturing Events in Poisson Point Processes
Mojmir Mutny, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7894-7904
Online Limited Memory Neural-Linear Bandits with Likelihood Matching
Ofir Nabati, Tom Zahavy, Shie Mannor; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7905-7915
Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7916-7926
GMAC: A Distributional Perspective on Actor-Critic Framework
Daniel W Nam, Younghoon Kim, Chan Y Park; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7927-7936
Memory-Efficient Pipeline-Parallel DNN Training
Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7937-7947
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7948-7957
Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, Peter Battaglia; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7958-7968
Geometric convergence of elliptical slice sampling
Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7969-7978
HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7979-7990
Emergent Social Learning via Multi-agent Reinforcement Learning
Kamal K Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:7991-8004
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Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8005-8015
Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8016-8024
Policy Caches with Successor Features
Mark Nemecek, Ronald Parr; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8025-8033
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
Elias Chaibub Neto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8034-8044
Incentivizing Compliance with Algorithmic Instruments
Dung Daniel T Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8045-8055
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh Nguyen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8056-8062
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Value-at-Risk Optimization with Gaussian Processes
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8063-8072
Cross-model Back-translated Distillation for Unsupervised Machine Translation
Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen, Kui Wu, Ai Ti Aw; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8073-8083
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8084-8095
Interactive Learning from Activity Description
Khanh X Nguyen, Dipendra Misra, Robert Schapire, Miroslav Dudik, Patrick Shafto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8096-8108
Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8109-8118
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido F Montufar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8119-8129
Temporal Predictive Coding For Model-Based Planning In Latent Space
Tung D Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8130-8139
Differentially Private Densest Subgraph Detection
Dung Nguyen, Anil Vullikanti; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8140-8151
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Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8152-8161
Improved Denoising Diffusion Probabilistic Models
Alexander Quinn Nichol, Prafulla Dhariwal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8162-8171
Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert, Ziv Goldfeld, Kengo Kato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8172-8183
AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8184-8194
Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction
Kenta Niwa, Guoqiang Zhang, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8195-8204
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, Taeho Yoon, Kwon Sehyun, Ernest K Ryu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8205-8215
The Impact of Record Linkage on Learning from Feature Partitioned Data
Richard Nock, Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8216-8226
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8227-8237
Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods
Chris Nota, Philip Thomas, Bruno C. Da Silva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8238-8247
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W Ober, Laurence Aitchison; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8248-8259
Regularizing towards Causal Invariance: Linear Models with Proxies
Michael Oberst, Nikolaj Thams, Jonas Peters, David Sontag; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8260-8270
Sparsity-Agnostic Lasso Bandit
Min-Hwan Oh, Garud Iyengar, Assaf Zeevi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8271-8280
Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, Yacov Hel-Or; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8281-8290
Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8291-8301
Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aaron Van Den Oord, Oriol Vinyals; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8302-8313
Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling
Ozan Özdenizci, Robert Legenstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8314-8324
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
Avik Pal, Yingbo Ma, Viral Shah, Christopher V Rackauckas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8325-8335
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RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8336-8348
Inference for Network Regression Models with Community Structure
Mengjie Pan, Tyler Mccormick, Bailey Fosdick; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8349-8358
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification
Bo Pang, Ying Nian Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8359-8370
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Leveraging Good Representations in Linear Contextual Bandits
Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8371-8380
Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8381-8390
Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8391-8400
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8401-8412
Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sung Woo Park, Dong Wook Shu, Junseok Kwon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8413-8421
Optimal Counterfactual Explanations in Tree Ensembles
Axel Parmentier, Thibaut Vidal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8422-8431
PHEW : Constructing Sparse Networks that Learn Fast and Generalize Well without Training Data
Shreyas Malakarjun Patil, Constantine Dovrolis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8432-8442
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
Anselm Paulus, Michal Rolinek, Vit Musil, Brandon Amos, Georg Martius; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8443-8453
Ensemble Bootstrapping for Q-Learning
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8454-8463
Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8464-8475
How could Neural Networks understand Programs?
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8476-8486
Privacy-Preserving Video Classification with Convolutional Neural Networks
Sikha Pentyala, Rafael Dowsley, Martine De Cock; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8487-8499
Rissanen Data Analysis: Examining Dataset Characteristics via Description Length
Ethan Perez, Douwe Kiela, Kyunghyun Cho; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8500-8513
Modelling Behavioural Diversity for Learning in Open-Ended Games
Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers, David H Mguni, Ying Wen, Jun Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8514-8524
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8525-8535
Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8536-8545
Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8546-8555
Megaverse: Simulating Embodied Agents at One Million Experiences per Second
Aleksei Petrenko, Erik Wijmans, Brennan Shacklett, Vladlen Koltun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8556-8566
Towards Practical Mean Bounds for Small Samples
My Phan, Philip Thomas, Erik Learned-Miller; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8567-8576
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs
Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8577-8587
GeomCA: Geometric Evaluation of Data Representations
Petra Poklukar, Anastasiia Varava, Danica Kragic; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8588-8598
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8599-8608
Bias-Free Scalable Gaussian Processes via Randomized Truncations
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P Cunningham; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8609-8619
Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset
Ilan Price, Jared Tanner; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8620-8629
BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Weizhu Chen, Dayiheng Liu, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8630-8639
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A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8640-8649
Global Prosody Style Transfer Without Text Transcriptions
Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David Cox, Mark Hasegawa-Johnson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8650-8660
Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8661-8671
Oneshot Differentially Private Top-k Selection
Gang Qiao, Weijie Su, Li Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8672-8681
Density Constrained Reinforcement Learning
Zengyi Qin, Yuxiao Chen, Chuchu Fan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8682-8692
Budgeted Heterogeneous Treatment Effect Estimation
Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8693-8702
Neural Transformation Learning for Deep Anomaly Detection Beyond Images
Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8703-8714
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8715-8725
Optimization Planning for 3D ConvNets
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8726-8736
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On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8737-8747
Learning Transferable Visual Models From Natural Language Supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8748-8763
A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8764-8775
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Muhammad A Rahman, Niklas Hopner, Filippos Christianos, Stefano V Albrecht; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8776-8786
Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8787-8798
Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia M Procopiuc, Claudio Gentile; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8799-8809
Differentially Private Sliced Wasserstein Distance
Alain Rakotomamonjy, Ralaivola Liva; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8810-8820
Zero-Shot Text-to-Image Generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8821-8831
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End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
Syama Sundar Rangapuram, Lucien D Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8832-8843
MSA Transformer
Roshan M Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8844-8856
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8857-8868
Generative Particle Variational Inference via Estimation of Functional Gradients
Neale Ratzlaff, Qinxun Bai, Li Fuxin, Wei Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8869-8879
Enhancing Robustness of Neural Networks through Fourier Stabilization
Netanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8880-8889
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Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
Ankit Singh Rawat, Aditya K Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Yu, Sashank Reddi, Sanjiv Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8890-8901
Cross-domain Imitation from Observations
Dripta S. Raychaudhuri, Sujoy Paul, Jeroen Vanbaar, Amit K. Roy-Chowdhury; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8902-8912
Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8913-8924
Align, then memorise: the dynamics of learning with feedback alignment
Maria Refinetti, Stéphane D’Ascoli, Ruben Ohana, Sebastian Goldt; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8925-8935
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8936-8947
Sharf: Shape-conditioned Radiance Fields from a Single View
Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8948-8958
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LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8959-8970
Interpreting and Disentangling Feature Components of Various Complexity from DNNs
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8971-8981
Integrated Defense for Resilient Graph Matching
Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8982-8997
Solving high-dimensional parabolic PDEs using the tensor train format
Lorenz Richter, Leon Sallandt, Nikolas Nüsken; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8998-9009
Best Arm Identification in Graphical Bilinear Bandits
Geovani Rizk, Albert Thomas, Igor Colin, Rida Laraki, Yann Chevaleyre; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9010-9019
Principled Simplicial Neural Networks for Trajectory Prediction
T. Mitchell Roddenberry, Nicholas Glaze, Santiago Segarra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9020-9029
On Linear Identifiability of Learned Representations
Geoffrey Roeder, Luke Metz, Durk Kingma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9030-9039
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data
Esther Rolf, Theodora T Worledge, Benjamin Recht, Michael Jordan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9040-9051
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9052-9063
Discretization Drift in Two-Player Games
Mihaela C Rosca, Yan Wu, Benoit Dherin, David Barrett; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9064-9074
On the Predictability of Pruning Across Scales
Jonathan S Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9075-9083
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
Andrew Ross, Finale Doshi-Velez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9084-9094
Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9095-9106
Multi-group Agnostic PAC Learnability
Guy N Rothblum, Gal Yona; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9107-9115
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9116-9126
An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9127-9135
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yangjun Ruan, Karen Ullrich, Daniel S Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris Maddison; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9136-9147
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes
Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9148-9156
Tilting the playing field: Dynamical loss functions for machine learning
Miguel Ruiz-Garcia, Ge Zhang, Samuel S Schoenholz, Andrea J. Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9157-9167
UnICORNN: A recurrent model for learning very long time dependencies
T. Konstantin Rusch, Siddhartha Mishra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9168-9178
Simple and Effective VAE Training with Calibrated Decoders
Oleh Rybkin, Kostas Daniilidis, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9179-9189
Model-Based Reinforcement Learning via Latent-Space Collocation
Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9190-9201
Training Data Subset Selection for Regression with Controlled Generalization Error
Durga S, Rishabh Iyer, Ganesh Ramakrishnan, Abir De; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9202-9212
Unsupervised Part Representation by Flow Capsules
Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey Hinton, David J Fleet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9213-9223
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Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9224-9234
Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9235-9244
Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9245-9254
Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9255-9264
Asymptotics of Ridge Regression in Convolutional Models
Mojtaba Sahraee-Ardakan, Tung Mai, Anup Rao, Ryan A. Rossi, Sundeep Rangan, Alyson K Fletcher; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9265-9275
Momentum Residual Neural Networks
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9276-9287
Meta-Learning Bidirectional Update Rules
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera Y Arcas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9288-9300
Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Elad Sarafian, Shai Keynan, Sarit Kraus; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9301-9312
Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9313-9322
E(n) Equivariant Graph Neural Networks
Vı́ctor Garcia Satorras, Emiel Hoogeboom, Max Welling; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9323-9332
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
Nikunj Saunshi, Arushi Gupta, Wei Hu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9333-9343
Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9344-9354
Linear Transformers Are Secretly Fast Weight Programmers
Imanol Schlag, Kazuki Irie, Jürgen Schmidhuber; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9355-9366
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M Schmidt, Frank Schneider, Philipp Hennig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9367-9376
Equivariant message passing for the prediction of tensorial properties and molecular spectra
Kristof Schütt, Oliver Unke, Michael Gastegger; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9377-9388
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9389-9398
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Connecting Sphere Manifolds Hierarchically for Regularization
Damien Scieur, Youngsung Kim; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9399-9409
Learning Intra-Batch Connections for Deep Metric Learning
Jenny Denise Seidenschwarz, Ismail Elezi, Laura Leal-Taixé; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9410-9421
Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N Hill, Inderjit S. Dhillon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9422-9433
Pure Exploration and Regret Minimization in Matching Bandits
Flore Sentenac, Jialin Yi, Clement Calauzenes, Vianney Perchet, Milan Vojnovic; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9434-9442
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State Entropy Maximization with Random Encoders for Efficient Exploration
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9443-9454
Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9455-9464
RRL: Resnet as representation for Reinforcement Learning
Rutav M Shah, Vikash Kumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9465-9476
Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9477-9488
Personalized Federated Learning using Hypernetworks
Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9489-9502
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On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise
Jie Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9503-9514
Sample-Optimal PAC Learning of Halfspaces with Malicious Noise
Jie Shen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9515-9524
Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
Guangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, Xiangyu Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9525-9536
State Relevance for Off-Policy Evaluation
Simon P Shen, Yecheng Ma, Omer Gottesman, Finale Doshi-Velez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9537-9546
SparseBERT: Rethinking the Importance Analysis in Self-attention
Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James Tin-Yau Kwok; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9547-9557
Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9558-9568
Segmenting Hybrid Trajectories using Latent ODEs
Ruian Shi, Quaid Morris; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9569-9579
Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9580-9591
GANMEX: One-vs-One Attributions using GAN-based Model Explainability
Sheng-Min Shih, Pin-Ju Tien, Zohar Karnin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9592-9602
Large-Scale Meta-Learning with Continual Trajectory Shifting
Jaewoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9603-9613
AGENT: A Benchmark for Core Psychological Reasoning
Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Joshua Tenenbaum, Tomer Ullman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9614-9625
Zoo-Tuning: Adaptive Transfer from A Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9626-9637
Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagné, Charles X Ling, Boyu Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9638-9648
Testing Group Fairness via Optimal Transport Projections
Nian Si, Karthyek Murthy, Jose Blanchet, Viet Anh Nguyen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9649-9659
On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan C Krishnan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9660-9670
A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9671-9680
Directed Graph Embeddings in Pseudo-Riemannian Manifolds
Aaron Sim, Maciej L Wiatrak, Angus Brayne, Paidi Creed, Saee Paliwal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9681-9690
Collaborative Bayesian Optimization with Fair Regret
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9691-9701
Dynamic Planning and Learning under Recovering Rewards
David Simchi-Levi, Zeyu Zheng, Feng Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9702-9711
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers
Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9712-9721
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9722-9732
Flow-based Attribution in Graphical Models: A Recursive Shapley Approach
Raghav Singal, George Michailidis, Hoiyi Ng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9733-9743
Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9744-9755
Skew Orthogonal Convolutions
Sahil Singla, Soheil Feizi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9756-9766
Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9767-9779
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm H Van Seijen, Mehdi Fatemi, Honglak Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9780-9790
Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving
Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9791-9800
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
Yuda Song, Wen Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9801-9811
Fast Sketching of Polynomial Kernels of Polynomial Degree
Zhao Song, David Woodruff, Zheng Yu, Lichen Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9812-9823
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
Chaobing Song, Stephen J Wright, Jelena Diakonikolas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9824-9834
Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9835-9847
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh A Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9848-9858
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet Des Combes; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9859-9869
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9870-9879
K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets
Xiu Su, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9880-9890
More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method
Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9891-9901
Not All Memories are Created Equal: Learning to Forget by Expiring
Sainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9902-9912
Nondeterminism and Instability in Neural Network Optimization
Cecilia Summers, Michael J. Dinneen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9913-9922
AutoSampling: Search for Effective Data Sampling Schedules
Ming Sun, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9923-9933
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What Makes for End-to-End Object Detection?
Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9934-9944
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9945-9954
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Gordon Gordon Wilson, Roger B Grosse; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9955-9965
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W Cohen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9966-9977
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PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9978-9988
Reinforcement Learning for Cost-Aware Markov Decision Processes
Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9989-9999
Model-Targeted Poisoning Attacks with Provable Convergence
Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10000-10010
Generalization Error Bound for Hyperbolic Ordinal Embedding
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10011-10021
Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10022-10032
Parallel tempering on optimized paths
Saifuddin Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Cote; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10033-10042
Robust Representation Learning via Perceptual Similarity Metrics
Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10043-10053
DriftSurf: Stable-State / Reactive-State Learning under Concept Drift
Ashraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phillip B Gibbons; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10054-10064
Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter D Bailis, Gregory Valiant; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10065-10075
Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10076-10085
Supervised Tree-Wasserstein Distance
Yuki Takezawa, Ryoma Sato, Makoto Yamada; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10086-10095
EfficientNetV2: Smaller Models and Faster Training
Mingxing Tan, Quoc Le; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10096-10106
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SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples
Anshoo Tandon, Aldric Han, Vincent Tan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10107-10117
1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10118-10129
Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10130-10140
REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, Tao Sun, Sunil Mallya; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10141-10152
Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
Salma Tarmoun, Guilherme Franca, Benjamin D Haeffele, Rene Vidal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10153-10161
Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man-Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10162-10172
A Language for Counterfactual Generative Models
Zenna Tavares, James Koppel, Xin Zhang, Ria Das, Armando Solar-Lezama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10173-10182
Synthesizer: Rethinking Self-Attention for Transformer Models
Yi Tay, Dara Bahri, Donald Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10183-10192
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OmniNet: Omnidirectional Representations from Transformers
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip M Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10193-10202
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T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP
Jiaye Teng, Zeren Tan, Yang Yuan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10203-10213
Moreau-Yosida $f$-divergences
Dávid Terjék; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10214-10224
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C Mozer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10225-10235
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph Gonzalez; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10236-10246
Monte Carlo Variational Auto-Encoders
Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10247-10257
Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model
Christian B Thygesen, Christian Skjødt Steenmans, Ahmad Salim Al-Sibahi, Lys Sanz Moreta, Anders Bundgård Sørensen, Thomas Hamelryck; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10258-10267
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Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10268-10278
Online Learning in Unknown Markov Games
Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10279-10288
BORE: Bayesian Optimization by Density-Ratio Estimation
Louis C Tiao, Aaron Klein, Matthias W Seeger, Edwin V. Bonilla, Cedric Archambeau, Fabio Ramos; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10289-10300
Nonparametric Decomposition of Sparse Tensors
Conor Tillinghast, Shandian Zhe; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10301-10311
Probabilistic Programs with Stochastic Conditioning
David Tolpin, Yuan Zhou, Tom Rainforth, Hongseok Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10312-10323
Deep Continuous Networks
Nergis Tomen, Silvia-Laura Pintea, Jan Van Gemert; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10324-10335
Diffusion Earth Mover’s Distance and Distribution Embeddings
Alexander Y Tong, Guillaume Huguet, Amine Natik, Kincaid Macdonald, Manik Kuchroo, Ronald Coifman, Guy Wolf, Smita Krishnaswamy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10336-10346
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, Herve Jegou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10347-10357
Conservative Objective Models for Effective Offline Model-Based Optimization
Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10358-10368
Sparse within Sparse Gaussian Processes using Neighbor Information
Gia-Lac Tran, Dimitrios Milios, Pietro Michiardi, Maurizio Filippone; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10369-10378
SMG: A Shuffling Gradient-Based Method with Momentum
Trang H Tran, Lam M Nguyen, Quoc Tran-Dinh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10379-10389
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10390-10400
On Disentangled Representations Learned from Correlated Data
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10401-10412
A New Formalism, Method and Open Issues for Zero-Shot Coordination
Johannes Treutlein, Michael Dennis, Caspar Oesterheld, Jakob Foerster; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10413-10423
Learning a Universal Template for Few-shot Dataset Generalization
Eleni Triantafillou, Hugo Larochelle, Richard Zemel, Vincent Dumoulin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10424-10433
Provable Meta-Learning of Linear Representations
Nilesh Tripuraneni, Chi Jin, Michael Jordan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10434-10443
Cumulants of Hawkes Processes are Robust to Observation Noise
William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10444-10454
PixelTransformer: Sample Conditioned Signal Generation
Shubham Tulsiani, Abhinav Gupta; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10455-10464
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A Framework for Private Matrix Analysis in Sliding Window Model
Jalaj Upadhyay, Sarvagya Upadhyay; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10465-10475
Fast Projection Onto Convex Smooth Constraints
Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Levy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10476-10486
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SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko, Liudmila Prokhorenkova; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10487-10496
LTL2Action: Generalizing LTL Instructions for Multi-Task RL
Pashootan Vaezipoor, Andrew C Li, Rodrigo A Toro Icarte, Sheila A. Mcilraith; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10497-10508
Active Deep Probabilistic Subsampling
Hans Van Gorp, Iris Huijben, Bastiaan S Veeling, Nicola Pezzotti, Ruud J. G. Van Sloun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10509-10518
CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Ramakrishna Vedantam, Arthur Szlam, Maximillian Nickel, Ari Morcos, Brenden M Lake; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10519-10529
Towards Domain-Agnostic Contrastive Learning
Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc Le; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10530-10541
Sparsifying Networks via Subdifferential Inclusion
Sagar Verma, Jean-Christophe Pesquet; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10542-10552
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol, Luke Metz, Jascha Sohl-Dickstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10553-10563
Online Graph Dictionary Learning
Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10564-10574
Neuro-algorithmic Policies Enable Fast Combinatorial Generalization
Marin Vlastelica, Michal Rolinek, Georg Martius; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10575-10585
Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10586-10595
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Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10596-10606
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Principal Component Hierarchy for Sparse Quadratic Programs
Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10607-10616
Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization
Neha Wadia, Daniel Duckworth, Samuel S Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10617-10629
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan C Wagener, Byron Boots, Ching-An Cheng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10630-10640
Task-Optimal Exploration in Linear Dynamical Systems
Andrew J Wagenmaker, Max Simchowitz, Kevin Jamieson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10641-10652
Learning and Planning in Average-Reward Markov Decision Processes
Yi Wan, Abhishek Naik, Richard S Sutton; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10653-10662
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A. Osborne; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10663-10674
Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Zi Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10675-10685
Fairness of Exposure in Stochastic Bandits
Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10686-10696
A Proxy Variable View of Shared Confounding
Yixin Wang, David Blei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10697-10707
Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss
Jiali Wang, He Chen, Rujun Jiang, Xudong Li, Zihao Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10708-10716
Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10717-10726
Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, Wenwu Zhu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10727-10737
Self-Tuning for Data-Efficient Deep Learning
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10738-10748
Label Distribution Learning Machine
Jing Wang, Xin Geng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10749-10759
AlphaNet: Improved Training of Supernets with Alpha-Divergence
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10760-10771
Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10772-10782
SG-PALM: a Fast Physically Interpretable Tensor Graphical Model
Yu Wang, Alfred Hero; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10783-10793
Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10794-10804
Robust Inference for High-Dimensional Linear Models via Residual Randomization
Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10805-10815
A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network
Jun-Kun Wang, Chi-Heng Lin, Jacob D Abernethy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10816-10827
Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method
Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10828-10838
ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10839-10848
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10849-10858
Robust Learning for Data Poisoning Attacks
Yunjuan Wang, Poorya Mianjy, Raman Arora; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10859-10869
SketchEmbedNet: Learning Novel Concepts by Imitating Drawings
Alexander Wang, Mengye Ren, Richard Zemel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10870-10881
Directional Bias Amplification
Angelina Wang, Olga Russakovsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10882-10893
An exact solver for the Weston-Watkins SVM subproblem
Yutong Wang, Clayton Scott; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10894-10904
SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao Song, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10905-10915
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10916-10926
Matrix Completion with Model-free Weighting
Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao, Kwun Chuen Gary Chan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10927-10936
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10937-10947
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Instabilities of Offline RL with Pre-Trained Neural Representation
Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham Kakade; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10948-10960
Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10961-10970
Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10971-10980
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10981-10990
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang, Han Zhao, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:10991-11002
Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11003-11012
Robust Asymmetric Learning in POMDPs
Andrew Warrington, Jonathan W Lavington, Adam Scibior, Mark Schmidt, Frank Wood; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11013-11023
A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11024-11034
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Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond
Dennis Wei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11035-11046
Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11047-11057
Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying Wei, Peilin Zhao, Junzhou Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11058-11067
A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting
Eli N Weinstein, Debora Marks; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11068-11079
Thinking Like Transformers
Gail Weiss, Yoav Goldberg, Eran Yahav; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11080-11090
Leveraged Weighted Loss for Partial Label Learning
Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11091-11100
Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11101-11111
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11112-11122
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Keyframe-Focused Visual Imitation Learning
Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11123-11133
Learning de-identified representations of prosody from raw audio
Jack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11134-11145
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Solving Inverse Problems with a Flow-based Noise Model
Jay Whang, Qi Lei, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11146-11157
Composing Normalizing Flows for Inverse Problems
Jay Whang, Erik Lindgren, Alex Dimakis; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11158-11169
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11170-11181
Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations
Mateusz Wilinski, Andrey Lokhov; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11182-11192
Leveraging Language to Learn Program Abstractions and Search Heuristics
Lionel Wong, Kevin M Ellis, Joshua Tenenbaum, Jacob Andreas; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11193-11204
Leveraging Sparse Linear Layers for Debuggable Deep Networks
Eric Wong, Shibani Santurkar, Aleksander Madry; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11205-11216
Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell C Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11217-11227
Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem Van De Meent; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11228-11239
Making Paper Reviewing Robust to Bid Manipulation Attacks
Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens Van Der Maaten, Kilian Weinberger; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11240-11250
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
Yuhuai Wu, Markus N Rabe, Wenda Li, Jimmy Ba, Roger B Grosse, Christian Szegedy; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11251-11262
ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11263-11273
Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11274-11284
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11285-11295
On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP
Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11296-11306
Generative Video Transformer: Can Objects be the Words?
Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11307-11318
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11319-11328
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach
Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11329-11339
Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Siegel, Nicolas Heess, Martin Riedmiller; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11340-11350
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11351-11361
On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11362-11371
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11372-11382
RNNRepair: Automatic RNN Repair via Model-based Analysis
Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou, Yang Liu, Xinyu Xing; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11383-11392
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
Annie Xie, James Harrison, Chelsea Finn; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11393-11403
Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11404-11413
Interaction-Grounded Learning
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11414-11423
Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization
Sang Michael Xie, Tengyu Ma, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11424-11435
Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11436-11447
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11448-11458
A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization
Ran Xin, Usman Khan, Soummya Kar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11459-11469
Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11470-11479
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CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin Liang, Guanghui Lan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11480-11491
To be Robust or to be Fair: Towards Fairness in Adversarial Training
Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain, Jiliang Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11492-11501
Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11502-11513
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11514-11524
Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11525-11536
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gomez-Bombarelli, Jian Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11537-11547
Self-supervised Graph-level Representation Learning with Local and Global Structure
Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11548-11558
Conformal prediction interval for dynamic time-series
Chen Xu, Yao Xie; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11559-11569
Learner-Private Convex Optimization
Jiaming Xu, Kuang Xu, Dana Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11570-11580
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11581-11591
Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth
Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11592-11602
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
Kan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11603-11612
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KNAS: Green Neural Architecture Search
Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu Sun, Hongxia Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11613-11625
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Structured Convolutional Kernel Networks for Airline Crew Scheduling
Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11626-11636
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11637-11647
EL-Attention: Memory Efficient Lossless Attention for Generation
Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11648-11658
Link Prediction with Persistent Homology: An Interactive View
Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11659-11669
CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11670-11681
On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, Rendong Ying, Chao Ma, Peilin Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11682-11692
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Tan, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11693-11703
Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11704-11715
Learning Optimal Auctions with Correlated Valuations from Samples
Chunxue Yang, Xiaohui Bei; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11716-11726
Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward J. Hu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11727-11737
LARNet: Lie Algebra Residual Network for Face Recognition
Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11738-11750
BASGD: Buffered Asynchronous SGD for Byzantine Learning
Yi-Rui Yang, Wu-Jun Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11751-11761
Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11762-11772
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11773-11783
Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11784-11794
Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J Ramadge; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11795-11807
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Chao-Han Huck Yang, Yun-Yun Tsai, Pin-Yu Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11808-11819
When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11820-11829
Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss
Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, Xiaopeng Zhang, Qi Tian; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11830-11841
Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, Yingcong Chen, Hao Wang, Dina Katabi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11842-11851
Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks
Yukun Yang, Wenrui Zhang, Peng Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11852-11862
SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
Lingxiao Yang, Ru-Yuan Zhang, Lida Li, Xiaohua Xie; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11863-11874
HAWQ-V3: Dyadic Neural Network Quantization
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael Mahoney, Kurt Keutzer; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11875-11886
Improving Generalization in Meta-learning via Task Augmentation
Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui () Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11887-11897
Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11898-11908
Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11909-11919
Reinforcement Learning with Prototypical Representations
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11920-11931
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Elementary superexpressive activations
Dmitry Yarotsky; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11932-11940
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Break-It-Fix-It: Unsupervised Learning for Program Repair
Michihiro Yasunaga, Percy Liang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11941-11952
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Improving Gradient Regularization using Complex-Valued Neural Networks
Eric C Yeats, Yiran Chen, Hai Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11953-11963
Neighborhood Contrastive Learning Applied to Online Patient Monitoring
Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11964-11974
From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11975-11986
Improved OOD Generalization via Adversarial Training and Pretraing
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11987-11997
Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl Johansson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11998-12008
Continuous-time Model-based Reinforcement Learning
Cagatay Yildiz, Markus Heinonen, Harri Lähdesmäki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12009-12018
Distributed Nyström Kernel Learning with Communications
Rong Yin, Weiping Wang, Dan Meng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12019-12028
Path Planning using Neural A* Search
Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12029-12039
SinIR: Efficient General Image Manipulation with Single Image Reconstruction
Jihyeong Yoo, Qifeng Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12040-12050
Conditional Temporal Neural Processes with Covariance Loss
Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12051-12061
Adversarial Purification with Score-based Generative Models
Jongmin Yoon, Sung Ju Hwang, Juho Lee; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12062-12072
Federated Continual Learning with Weighted Inter-client Transfer
Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12073-12086
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Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Park; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12087-12097
Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm
Taeho Yoon, Ernest K Ryu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12098-12109
Lower-Bounded Proper Losses for Weakly Supervised Classification
Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12110-12120
Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12121-12132
LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12133-12143
Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12144-12155
DAGs with No Curl: An Efficient DAG Structure Learning Approach
Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12156-12166
Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12167-12176
Whittle Networks: A Deep Likelihood Model for Time Series
Zhongjie Yu, Fabrizio G Ventola, Kristian Kersting; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12177-12186
Deep Latent Graph Matching
Tianshu Yu, Runzhong Wang, Junchi Yan, Baoxin Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12187-12197
Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
Jiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, Byungin Yoo, Jae-Joon Han; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12198-12207
Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12208-12218
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12219-12229
Neural Tangent Generalization Attacks
Chia-Hung Yuan, Shan-Hung Wu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12230-12240
On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12241-12252
Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Reddi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12253-12266
Three Operator Splitting with a Nonconvex Loss Function
Alp Yurtsever, Varun Mangalick, Suvrit Sra; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12267-12277
Grey-box Extraction of Natural Language Models
Santiago Zanella-Beguelin, Shruti Tople, Andrew Paverd, Boris Köpf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12278-12286
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12287-12297
Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt Kusner, Vlad Niculae; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12298-12309
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stephane Deny; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12310-12320
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
Zhanpeng Zeng, Yunyang Xiong, Sathya Ravi, Shailesh Acharya, Glenn M Fung, Vikas Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12321-12332
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12333-12344
DORO: Distributional and Outlier Robust Optimization
Runtian Zhai, Chen Dan, Zico Kolter, Pradeep Ravikumar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12345-12355
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12356-12367
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12368-12379
Efficient Lottery Ticket Finding: Less Data is More
Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12380-12390
Robust Policy Gradient against Strong Data Corruption
Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12391-12401
Near Optimal Reward-Free Reinforcement Learning
Zihan Zhang, Simon Du, Xiangyang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12402-12412
Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12413-12426
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Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily Zhang, Mark Goldstein, Rajesh Ranganath; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12427-12436
Poolingformer: Long Document Modeling with Pooling Attention
Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Weizhu Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12437-12446
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Probabilistic Generating Circuits
Honghua Zhang, Brendan Juba, Guy Van Den Broeck; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12447-12457
PAPRIKA: Private Online False Discovery Rate Control
Wanrong Zhang, Gautam Kamath, Rachel Cummings; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12458-12467
Learning from Noisy Labels with No Change to the Training Process
Mingyuan Zhang, Jane Lee, Shivani Agarwal; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12468-12478
Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation
Jiawei Zhang, Linyi Li, Huichen Li, Xiaolu Zhang, Shuang Yang, Bo Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12479-12490
FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning
Tianhao Zhang, Yueheng Li, Chen Wang, Guangming Xie, Zongqing Lu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12491-12500
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Yivan Zhang, Gang Niu, Masashi Sugiyama; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12501-12512
Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12513-12523
Towards Better Robust Generalization with Shift Consistency Regularization
Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12524-12534
On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith W Ross; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12535-12545
Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution
Zhaoyang Zhang, Wenqi Shao, Jinwei Gu, Xiaogang Wang, Ping Luo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12546-12556
iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven W. Su, Shirui Pan, Xiaojun Chang, Ehsan M Abbasnejad, Reza Haffari; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12557-12566
Deep Coherent Exploration for Continuous Control
Yijie Zhang, Herke Van Hoof; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12567-12577
Average-Reward Off-Policy Policy Evaluation with Function Approximation
Shangtong Zhang, Yi Wan, Richard S Sutton, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12578-12588
Matrix Sketching for Secure Collaborative Machine Learning
Mengjiao Zhang, Shusen Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12589-12599
MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
Jin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12600-12610
World Model as a Graph: Learning Latent Landmarks for Planning
Lunjun Zhang, Ge Yang, Bradly C Stadie; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12611-12620
Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12621-12631
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Y Hou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12632-12641
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
Qian Zhang, Yilin Zheng, Jean Honorio; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12642-12652
Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
Zihan Zhang, Yuan Zhou, Xiangyang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12653-12662
Learning to Rehearse in Long Sequence Memorization
Zhu Zhang, Chang Zhou, Jianxin Ma, Zhijie Lin, Jingren Zhou, Hongxia Yang, Zhou Zhao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12663-12673
Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12674-12685
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Joining datasets via data augmentation in the label space for neural networks
Junbo Zhao, Mingfeng Ou, Linji Xue, Yunkai Cui, Sai Wu, Gang Chen; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12686-12696
Calibrate Before Use: Improving Few-shot Performance of Language Models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12697-12706
Few-Shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12707-12718
Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12719-12735
Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation
Renjie Zheng, Junkun Chen, Mingbo Ma, Liang Huang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12736-12746
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Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination
Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12747-12760
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How Framelets Enhance Graph Neural Networks
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montufar; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12761-12771
Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions
Zixin Zhong, Wang Chi Cheung, Vincent Tan; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12772-12781
Towards Distraction-Robust Active Visual Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12782-12792
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12793-12802
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation
Aurick Zhou, Sergey Levine; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12803-12812
Optimal Estimation of High Dimensional Smooth Additive Function Based on Noisy Observations
Fan Zhou, Ping Li; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12813-12823
Incentivized Bandit Learning with Self-Reinforcing User Preferences
Tianchen Zhou, Jia Liu, Chaosheng Dong, Jingyuan Deng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12824-12834
Towards Defending against Adversarial Examples via Attack-Invariant Features
Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12835-12845
Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12846-12856
Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12857-12867
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12868-12877
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12878-12889
Spectral vertex sparsifiers and pair-wise spanners over distributed graphs
Chunjiang Zhu, Qinqing Liu, Jinbo Bi; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12890-12900
Few-shot Language Coordination by Modeling Theory of Mind
Hao Zhu, Graham Neubig, Yonatan Bisk; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12901-12911
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
Zhaowei Zhu, Yiwen Song, Yang Liu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12912-12923
Commutative Lie Group VAE for Disentanglement Learning
Xinqi Zhu, Chang Xu, Dacheng Tao; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12924-12934
Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural Networks
Huiping Zhuang, Zhenyu Weng, Fulin Luo, Toh Kar-Ann, Haizhou Li, Zhiping Lin; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12935-12944
Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12945-12954
Recovering AES Keys with a Deep Cold Boot Attack
Itamar Zimerman, Eliya Nachmani, Lior Wolf; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12955-12966
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Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12967-12978
Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12979-12990
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa M Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:12991-13001
Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou, Spencer Frei, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:13002-13011
On the Convergence of Hamiltonian Monte Carlo with Stochastic Gradients
Difan Zou, Quanquan Gu; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:13012-13022
A Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna; Proceedings of the 38th International Conference on Machine Learning, PMLR 139:13023-13032
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