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Editors: Jennifer Dy, Andreas Krause
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Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems
; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1-9
State Abstractions for Lifelong Reinforcement Learning
David Abel, Dilip Arumugam, Lucas Lehnert, Michael Littman; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:10-19
Policy and Value Transfer in Lifelong Reinforcement Learning
David Abel, Yuu Jinnai, Sophie Yue Guo, George Konidaris, Michael Littman; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:20-29
INSPECTRE: Privately Estimating the Unseen
Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:30-39
Learning Representations and Generative Models for 3D Point Clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, Leonidas Guibas; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:40-49
Discovering Interpretable Representations for Both Deep Generative and Discriminative Models
Tameem Adel, Zoubin Ghahramani, Adrian Weller; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:50-59
A Reductions Approach to Fair Classification
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudik, John Langford, Hanna Wallach; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:60-69
Accelerated Spectral Ranking
Arpit Agarwal, Prathamesh Patil, Shivani Agarwal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:70-79
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches
Amirali Aghazadeh, Ryan Spring, Daniel Lejeune, Gautam Dasarathy, Anshumali Shrivastava, baraniuk; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:80-88
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
Raj Agrawal, Caroline Uhler, Tamara Broderick; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:89-98
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy
Shipra Agrawal, Morteza Zadimoghaddam, Vahab Mirrokni; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:99-108
Bucket Renormalization for Approximate Inference
Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:109-118
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee, Emily B. Fox; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:119-128
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design
Ahmed Alaa, Mihaela Schaar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:129-138
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
Ahmed Alaa, Mihaela Schaar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:139-148
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization
Ibrahim Alabdulmohsin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:149-158
Fixing a Broken ELBO
Alexander Alemi, Ben Poole, Ian Fischer, Joshua Dillon, Rif A. Saurous, Kevin Murphy; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:159-168
Differentially Private Identity and Equivalence Testing of Discrete Distributions
Maryam Aliakbarpour, Ilias Diakonikolas, Ronitt Rubinfeld; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:169-178
Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization
Zeyuan Allen-Zhu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:179-185
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Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
Zeyuan Allen-Zhu, Sebastien Bubeck, Yuanzhi Li; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:186-194
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Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Amjad Almahairi, Sai Rajeshwar, Alessandro Sordoni, Philip Bachman, Aaron Courville; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:195-204
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Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
Ron Amit, Ron Meir; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:205-214
MAGAN: Aligning Biological Manifolds
Matthew Amodio, Smita Krishnaswamy; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:215-223
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Subspace Embedding and Linear Regression with Orlicz Norm
Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:224-233
Efficient Gradient-Free Variational Inference using Policy Search
Oleg Arenz, Gerhard Neumann, Mingjun Zhong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:234-243
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
Sanjeev Arora, Nadav Cohen, Elad Hazan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:244-253
Stronger Generalization Bounds for Deep Nets via a Compression Approach
Sanjeev Arora, Rong Ge, Behnam Neyshabur, Yi Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:254-263
Lipschitz Continuity in Model-based Reinforcement Learning
Kavosh Asadi, Dipendra Misra, Michael Littman; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:264-273
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye, Nicholas Carlini, David Wagner; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:274-283
Synthesizing Robust Adversarial Examples
Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:284-293
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing
Davide Bacciu, Federico Errica, Alessio Micheli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:294-303
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Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
Wenruo Bai, Jeff Bilmes; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:304-313
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
Marco Baity-Jesi, Levent Sagun, Mario Geiger, Stefano Spigler, Gerard Ben Arous, Chiara Cammarota, Yann LeCun, Matthieu Wyart, Giulio Biroli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:314-323
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SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
Chandrajit Bajaj, Tingran Gao, Zihang He, Qixing Huang, Zhenxiao Liang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:324-333
A Boo(n) for Evaluating Architecture Performance
Ondrej Bajgar, Rudolf Kadlec, Jan Kleindienst; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:334-343
Learning to Branch
Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:344-353
The Mechanics of n-Player Differentiable Games
David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:354-363
Spline Filters For End-to-End Deep Learning
Randall Balestriero, Romain Cosentino, Herve Glotin, Richard Baraniuk; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:364-373
A Spline Theory of Deep Learning
Randall Balestriero, baraniuk; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:374-383
Approximation Guarantees for Adaptive Sampling
Eric Balkanski, Yaron Singer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:384-393
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
Borja Balle, Yu-Xiang Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:394-403
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
Lukas Balles, Philipp Hennig; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:404-413
Differentially Private Database Release via Kernel Mean Embeddings
Matej Balog, Ilya Tolstikhin, Bernhard Schölkopf; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:414-422
Improving Optimization for Models With Continuous Symmetry Breaking
Robert Bamler, Stephan Mandt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:423-432
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Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang, Hyunjung Shim; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:433-442
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Using Inherent Structures to design Lean 2-layer RBMs
Abhishek Bansal, Abhinav Anand, Chiranjib Bhattacharyya; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:443-451
Classification from Pairwise Similarity and Unlabeled Data
Han Bao, Gang Niu, Masashi Sugiyama; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:452-461
Bayesian Optimization of Combinatorial Structures
Ricardo Baptista, Matthias Poloczek; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:462-471
Geodesic Convolutional Shape Optimization
Pierre Baque, Edoardo Remelli, Francois Fleuret, Pascal Fua; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:472-481
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
Eugenio Bargiacchi, Timothy Verstraeten, Diederik Roijers, Ann Nowé, Hado Hasselt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:482-490
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Testing Sparsity over Known and Unknown Bases
Siddharth Barman, Arnab Bhattacharyya, Suprovat Ghoshal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:491-500
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
Andre Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel Mankowitz, Augustin Zidek, Remi Munos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:501-510
Measuring abstract reasoning in neural networks
David Barrett, Felix Hill, Adam Santoro, Ari Morcos, Timothy Lillicrap; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:511-520
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
Peter Bartlett, Dave Helmbold, Philip Long; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:521-530
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Mutual Information Neural Estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, Devon Hjelm; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:531-540
To Understand Deep Learning We Need to Understand Kernel Learning
Mikhail Belkin, Siyuan Ma, Soumik Mandal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:541-549
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Understanding and Simplifying One-Shot Architecture Search
Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, Quoc Le; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:550-559
signSGD: Compressed Optimisation for Non-Convex Problems
Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:560-569
Distributed Clustering via LSH Based Data Partitioning
Aditya Bhaskara, Maheshakya Wijewardena; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:570-579
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
Mikolaj Binkowski, Gautier Marti, Philippe Donnat; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:580-589
Adaptive Sampled Softmax with Kernel Based Sampling
Guy Blanc, Steffen Rendle; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:590-599
Optimizing the Latent Space of Generative Networks
Piotr Bojanowski, Armand Joulin, David Lopez-Pas, Arthur Szlam; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:600-609
NetGAN: Generating Graphs via Random Walks
Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:610-619
A Progressive Batching L-BFGS Method for Machine Learning
Raghu Bollapragada, Jorge Nocedal, Dheevatsa Mudigere, Hao-Jun Shi, Ping Tak Peter Tang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:620-629
Prediction Rule Reshaping
Matt Bonakdarpour, Sabyasachi Chatterjee, Rina Foygel Barber, John Lafferty; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:630-638
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QuantTree: Histograms for Change Detection in Multivariate Data Streams
Giacomo Boracchi, Diego Carrera, Cristiano Cervellera, Danilo Macciò; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:639-648
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
Vladimir Braverman, Stephen Chestnut, Robert Krauthgamer, Yi Li, David Woodruff, Lin Yang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:649-658
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Predict and Constrain: Modeling Cardinality in Deep Structured Prediction
Nataly Brukhim, Amir Globerson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:659-667
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Quasi-Monte Carlo Variational Inference
Alexander Buchholz, Florian Wenzel, Stephan Mandt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:668-677
Path-Level Network Transformation for Efficient Architecture Search
Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, Yong Yu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:678-687
Improved large-scale graph learning through ridge spectral sparsification
Daniele Calandriello, Alessandro Lazaric, Ioannis Koutis, Michal Valko; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:688-697
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
Trevor Campbell, Tamara Broderick; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:698-706
Adversarial Learning with Local Coordinate Coding
Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:707-715
Fair and Diverse DPP-Based Data Summarization
Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, Nisheeth Vishnoi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:716-725
Conditional Noise-Contrastive Estimation of Unnormalised Models
Ciwan Ceylan, Michael U. Gutmann; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:726-734
Adversarial Time-to-Event Modeling
Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Goldstein, Lawrence Carin Duke, Ricardo Henao; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:735-744
Stability and Generalization of Learning Algorithms that Converge to Global Optima
Zachary Charles, Dimitris Papailiopoulos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:745-754
Learning and Memorization
Satrajit Chatterjee; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:755-763
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
Niladri Chatterji, Nicolas Flammarion, Yian Ma, Peter Bartlett, Michael Jordan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:764-773
Hierarchical Clustering with Structural Constraints
Vaggos Chatziafratis, Rad Niazadeh, Moses Charikar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:774-783
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
Zhengping Che, Sanjay Purushotham, Guangyu Li, Bo Jiang, Yan Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:784-793
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen, Vijay Badrinarayanan, Chen-Yu Lee, Andrew Rabinovich; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:794-803
Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?
Lin Chen, Moran Feldman, Amin Karbasi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:804-813
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:814-823
Continuous-Time Flows for Efficient Inference and Density Estimation
Changyou Chen, Chunyuan Li, Liqun Chen, Wenlin Wang, Yunchen Pu, Lawrence Carin Duke; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:824-833
Scalable Bilinear Pi Learning Using State and Action Features
Yichen Chen, Lihong Li, Mengdi Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:834-843
Stein Points
Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris Oates; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:844-853
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations
Ting Chen, Martin Renqiang Min, Yizhou Sun; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:854-863
PixelSNAIL: An Improved Autoregressive Generative Model
XI Chen, Nikhil Mishra, Mostafa Rohaninejad, Pieter Abbeel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:864-872
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Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Minmin Chen, Jeffrey Pennington, Samuel Schoenholz; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:873-882
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
Jianbo Chen, Le Song, Martin Wainwright, Michael Jordan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:883-892
Variational Inference and Model Selection with Generalized Evidence Bounds
Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin Duke; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:893-902
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:903-912
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
Zaiyi Chen, Yi Xu, Enhong Chen, Tianbao Yang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:913-921
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Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization
Jinghui Chen, Pan Xu, Lingxiao Wang, Jian Ma, Quanquan Gu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:922-931
End-to-End Learning for the Deep Multivariate Probit Model
Di Chen, Yexiang Xue, Carla Gomes; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:932-941
Stochastic Training of Graph Convolutional Networks with Variance Reduction
Jianfei Chen, Jun Zhu, Le Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:942-950
Extreme Learning to Rank via Low Rank Assumption
Minhao Cheng, Ian Davidson, Cho-Jui Hsieh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:951-960
Learning a Mixture of Two Multinomial Logits
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:961-969
Structured Evolution with Compact Architectures for Scalable Policy Optimization
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard Turner, Adrian Weller; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:970-978
Path Consistency Learning in Tsallis Entropy Regularized MDPs
Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:979-988
An Iterative, Sketching-based Framework for Ridge Regression
Agniva Chowdhury, Jiasen Yang, Petros Drineas; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:989-998
Stochastic Wasserstein Barycenters
Sebastian Claici, Edward Chien, Justin Solomon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:999-1008
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Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
John Co-Reyes, YuXuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1009-1018
On Acceleration with Noise-Corrupted Gradients
Michael Cohen, Jelena Diakonikolas, Lorenzo Orecchia; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1019-1028
Online Linear Quadratic Control
Alon Cohen, Avinatan Hasidim, Tomer Koren, Nevena Lazic, Yishay Mansour, Kunal Talwar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1029-1038
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1039-1048
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Dane Corneil, Wulfram Gerstner, Johanni Brea; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1049-1058
Online Learning with Abstention
Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Scott Yang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1059-1067
Constrained Interacting Submodular Groupings
Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya Gupta, Jeff Bilmes; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1068-1077
Inference Suboptimality in Variational Autoencoders
Chris Cremer, Xuechen Li, David Duvenaud; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1078-1086
Mix & Match Agent Curricula for Reinforcement Learning
Wojciech Czarnecki, Siddhant Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Nicolas Heess, Simon Osindero, Razvan Pascanu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1087-1095
Implicit Quantile Networks for Distributional Reinforcement Learning
Will Dabney, Georg Ostrovski, David Silver, Remi Munos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1096-1105
Learning Steady-States of Iterative Algorithms over Graphs
Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alex Smola, Le Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1106-1114
Adversarial Attack on Graph Structured Data
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1115-1124
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SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1125-1134
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Compressing Neural Networks using the Variational Information Bottleneck
Bin Dai, Chen Zhu, Baining Guo, David Wipf; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1135-1144
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Asynchronous Byzantine Machine Learning (the case of SGD)
Georgios Damaskinos, El-Mahdi El-Mhamdi, Rachid Guerraoui, Rhicheek Patra, Mahsa Taziki; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1145-1154
Escaping Saddles with Stochastic Gradients
Hadi Daneshmand, Jonas Kohler, Aurelien Lucchi, Thomas Hofmann; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1155-1164
Minibatch Gibbs Sampling on Large Graphical Models
Chris De Sa, Vincent Chen, Wing Wong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1165-1173
Stochastic Video Generation with a Learned Prior
Emily Denton, Rob Fergus; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1174-1183
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Stefan Depeweg, Jose-Miguel Hernandez-Lobato, Finale Doshi-Velez, Steffen Udluft; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1184-1193
Accurate Inference for Adaptive Linear Models
Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1194-1203
Variational Network Inference: Strong and Stable with Concrete Support
Amir Dezfouli, Edwin Bonilla, Richard Nock; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1204-1213
Modeling Sparse Deviations for Compressed Sensing using Generative Models
Manik Dhar, Aditya Grover, Stefano Ermon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1214-1223
Alternating Randomized Block Coordinate Descent
Jelena Diakonikolas, Lorenzo Orecchia; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1224-1232
Learning to Act in Decentralized Partially Observable MDPs
Jilles Dibangoye, Olivier Buffet; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1233-1242
Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms
Charlie Dickens, Graham Cormode, David Woodruff; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1243-1251
Noisin: Unbiased Regularization for Recurrent Neural Networks
Adji Bousso Dieng, Rajesh Ranganath, Jaan Altosaar, David Blei; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1252-1261
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Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
Thomas Dietterich, George Trimponias, Zhitang Chen; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1262-1270
Coordinated Exploration in Concurrent Reinforcement Learning
Maria Dimakopoulou, Benjamin Van Roy; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1271-1279
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Probabilistic Recurrent State-Space Models
Andreas Doerr, Christian Daniel, Martin Schiegg, Nguyen-Tuong Duy, Stefan Schaal, Marc Toussaint, Trimpe Sebastian; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1280-1289
Randomized Block Cubic Newton Method
Nikita Doikov, Peter Richtarik, University Edinburgh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1290-1298
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
Ahmed Douik, Babak Hassibi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1299-1308
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Essentially No Barriers in Neural Network Energy Landscape
Felix Draxler, Kambis Veschgini, Manfred Salmhofer, Fred Hamprecht; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1309-1318
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
Alexey Drutsa; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1319-1328
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
Simon Du, Jason Lee; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1329-1338
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Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima
Simon Du, Jason Lee, Yuandong Tian, Aarti Singh, Barnabas Poczos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1339-1348
Investigating Human Priors for Playing Video Games
Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Tom Griffiths, Alexei Efros; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1349-1357
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A Distributed Second-Order Algorithm You Can Trust
Celestine Duenner, Aurelien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1358-1366
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn’s Algorithm
Pavel Dvurechensky, Alexander Gasnikov, Alexey Kroshnin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1367-1376
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite, Daniel Roy; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1377-1386
Beyond the One-Step Greedy Approach in Reinforcement Learning
Yonathan Efroni, Gal Dalal, Bruno Scherrer, Shie Mannor; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1387-1396
Parallel and Streaming Algorithms for K-Core Decomposition
Hossein Esfandiari, Silvio Lattanzi, Vahab Mirrokni; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1397-1406
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IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Lasse Espeholt, Hubert Soyer, Remi Munos, Karen Simonyan, Vlad Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1407-1416
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor Evans, Prasanth Nair; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1417-1426
The Limits of Maxing, Ranking, and Preference Learning
Moein Falahatgar, Ayush Jain, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1427-1436
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
Stefan Falkner, Aaron Klein, Frank Hutter; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1437-1446
More Robust Doubly Robust Off-policy Evaluation
Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1447-1456
Efficient and Consistent Adversarial Bipartite Matching
Rizal Fathony, Sima Behpour, Xinhua Zhang, Brian Ziebart; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1457-1466
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel, Rong Ge, Sham Kakade, Mehran Mesbahi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1467-1476
CRVI: Convex Relaxation for Variational Inference
Ghazal Fazelnia, John Paisley; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1477-1485
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Fourier Policy Gradients
Matthew Fellows, Kamil Ciosek, Shimon Whiteson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1486-1495
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng, Brian Williamson, Noah Simon, Marco Carone; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1496-1505
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
Louis Filstroff, Alberto Lumbreras, Cédric Févotte; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1506-1514
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Automatic Goal Generation for Reinforcement Learning Agents
Carlos Florensa, David Held, Xinyang Geng, Pieter Abbeel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1515-1528
DiCE: The Infinitely Differentiable Monte Carlo Estimator
Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric Xing, Shimon Whiteson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1529-1538
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Practical Contextual Bandits with Regression Oracles
Dylan Foster, Alekh Agarwal, Miroslav Dudik, Haipeng Luo, Robert Schapire; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1539-1548
Generative Temporal Models with Spatial Memory for Partially Observed Environments
Marco Fraccaro, Danilo Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1549-1558
ADMM and Accelerated ADMM as Continuous Dynamical Systems
Guilherme Franca, Daniel Robinson, Rene Vidal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1559-1567
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Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi, Paolo Frasconi, Saverio Salzo, Riccardo Grazzi, Massimiliano Pontil; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1568-1577
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1578-1586
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto, Herke Hoof, David Meger; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1587-1596
Clipped Action Policy Gradient
Yasuhiro Fujita, Shin-ichi Maeda; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1597-1606
Born Again Neural Networks
Tommaso Furlanello, Zachary Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1607-1616
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The Generalization Error of Dictionary Learning with Moreau Envelopes
Alexandros Georgogiannis; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1617-1625
Local Private Hypothesis Testing: Chi-Square Tests
Marco Gaboardi, Ryan Rogers; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1626-1635
Inductive Two-Layer Modeling with Parametric Bregman Transfer
Vignesh Ganapathiraman, Zhan Shi, Xinhua Zhang, Yaoliang Yu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1636-1645
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings
Octavian Ganea, Gary Becigneul, Thomas Hofmann; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1646-1655
Parameterized Algorithms for the Matrix Completion Problem
Robert Ganian, Iyad Kanj, Sebastian Ordyniak, Stefan Szeider; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1656-1665
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Synthesizing Programs for Images using Reinforced Adversarial Learning
Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1666-1675
Spotlight: Optimizing Device Placement for Training Deep Neural Networks
Yuanxiang Gao, Li Chen, Baochun Li; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1676-1684
Parallel Bayesian Network Structure Learning
Tian Gao, Dennis Wei; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1685-1694
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Alexandre Garcia, Chloé Clavel, Slim Essid, Florence d’Alche-Buc; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1695-1703
Conditional Neural Processes
Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Rezende, S. M. Ali Eslami; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1704-1713
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Temporal Poisson Square Root Graphical Models
Sinong Geng, Zhaobin Kuang, Peggy Peissig, David Page; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1714-1723
Budgeted Experiment Design for Causal Structure Learning
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1724-1733
Linear Spectral Estimators and an Application to Phase Retrieval
Ramina Ghods, Andrew Lan, Tom Goldstein, Christoph Studer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1734-1743
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1744-1753
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
Asish Ghoshal, Jean Honorio; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1754-1762
Robust and Scalable Models of Microbiome Dynamics
Travis Gibson, Georg Gerber; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1763-1772
Non-linear motor control by local learning in spiking neural networks
Aditya Gilra, Wulfram Gerstner; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1773-1782
Learning One Convolutional Layer with Overlapping Patches
Surbhi Goel, Adam Klivans, Raghu Meka; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1783-1791
Visualizing and Understanding Atari Agents
Samuel Greydanus, Anurag Koul, Jonathan Dodge, Alan Fern; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1792-1801
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Learning Policy Representations in Multiagent Systems
Aditya Grover, Maruan Al-Shedivat, Jayesh Gupta, Yuri Burda, Harrison Edwards; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1802-1811
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines
Bin Gu, Zhouyuan Huo, Cheng Deng, Heng Huang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1812-1821
Learning to search with MCTSnets
Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Remi Munos, David Silver; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1822-1831
Characterizing Implicit Bias in Terms of Optimization Geometry
Suriya Gunasekar, Jason Lee, Daniel Soudry, Nathan Srebro; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1832-1841
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta, Tomer Koren, Yoram Singer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1842-1850
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Latent Space Policies for Hierarchical Reinforcement Learning
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, Sergey Levine; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1851-1860
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1861-1870
Comparison-Based Random Forests
Siavash Haghiri, Damien Garreau, Ulrike Luxburg; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1871-1880
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm, Yung-Kyun Noh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1881-1889
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
Lei Han, Yiheng Huang, Tong Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1890-1899
Stein Variational Gradient Descent Without Gradient
Jun Han, Qiang Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1900-1908
Deep Models of Interactions Across Sets
Jason Hartford, Devon Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1909-1918
Learning Memory Access Patterns
Milad Hashemi, Kevin Swersky, Jamie Smith, Grant Ayers, Heiner Litz, Jichuan Chang, Christos Kozyrakis, Parthasarathy Ranganathan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1919-1928
Fairness Without Demographics in Repeated Loss Minimization
Tatsunori Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1929-1938
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
Ursula Hebert-Johnson, Michael Kim, Omer Reingold, Guy Rothblum; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1939-1948
Recurrent Predictive State Policy Networks
Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha Srinivasa, Geoffrey Gordon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1949-1958
Learning unknown ODE models with Gaussian processes
Markus Heinonen, Cagatay Yildiz, Henrik Mannerström, Jukka Intosalmi, Harri Lähdesmäki; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1959-1968
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform
Kyle Helfrich, Devin Willmott, Qiang Ye; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1969-1978
Fast Bellman Updates for Robust MDPs
Chin Pang Ho, Marek Petrik, Wolfram Wiesemann; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1979-1988
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei Efros, Trevor Darrell; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1989-1998
Sound Abstraction and Decomposition of Probabilistic Programs
Steven Holtzen, Guy Broeck, Todd Millstein; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1999-2008
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
Mingyi Hong, Meisam Razaviyayn, Jason Lee; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2009-2018
Variational Bayesian dropout: pitfalls and fixes
Jiri Hron, Alex Matthews, Zoubin Ghahramani; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2019-2028
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Weihua Hu, Gang Niu, Issei Sato, Masashi Sugiyama; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2029-2037
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
Bin Hu, Stephen Wright, Laurent Lessard; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2038-2047
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
Zengfeng Huang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2048-2057
Learning Deep ResNet Blocks Sequentially using Boosting Theory
Furong Huang, Jordan Ash, John Langford, Robert Schapire; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2058-2067
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
Kejun Huang, Xiao Fu, Nicholas Sidiropoulos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2068-2077
Neural Autoregressive Flows
Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron Courville; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2078-2087
Topological mixture estimation
Steve Huntsman; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2088-2097
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Decoupled Parallel Backpropagation with Convergence Guarantee
Zhouyuan Huo, Bin Gu, Yang, Heng Huang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2098-2106
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
Rodrigo Toro Icarte, Toryn Klassen, Richard Valenzano, Sheila McIlraith; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2107-2116
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl, Luisa Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2117-2126
Attention-based Deep Multiple Instance Learning
Maximilian Ilse, Jakub Tomczak, Max Welling; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2127-2136
Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2137-2146
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Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model
Hideaki Imamura, Issei Sato, Masashi Sugiyama; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2147-2156
Improving Regression Performance with Distributional Losses
Ehsan Imani, Martha White; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2157-2166
Deep Density Destructors
David Inouye, Pradeep Ravikumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2167-2175
Unbiased Objective Estimation in Predictive Optimization
Shinji Ito, Akihiro Yabe, Ryohei Fujimaki; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2176-2185
Anonymous Walk Embeddings
Sergey Ivanov, Evgeny Burnaev; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2186-2195
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Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
Ariel Jaffe, Roi Weiss, Boaz Nadler, Shai Carmi, Yuval Kluger; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2196-2205
Firing Bandits: Optimizing Crowdfunding
Lalit Jain, Kevin Jamieson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2206-2214
Differentially Private Matrix Completion Revisited
Prateek Jain, Om Dipakbhai Thakkar, Abhradeep Thakurta; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2215-2224
Video Prediction with Appearance and Motion Conditions
Yunseok Jang, Gunhee Kim, Yale Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2225-2234
Pathwise Derivatives Beyond the Reparameterization Trick
Martin Jankowiak, Fritz Obermeyer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2235-2244
Detecting non-causal artifacts in multivariate linear regression models
Dominik Janzing, Bernhard Schölkopf; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2245-2253
A Unified Framework for Structured Low-rank Matrix Learning
Pratik Jawanpuria, Bamdev Mishra; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2254-2263
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Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong, Hyun Oh Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2264-2273
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Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
Zhihao Jia, Sina Lin, Charles R. Qi, Alex Aiken; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2274-2283
Feedback-Based Tree Search for Reinforcement Learning
Daniel Jiang, Emmanuel Ekwedike, Han Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2284-2293
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
Heinrich Jiang, Jennifer Jang, Samory Kpotufe; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2294-2303
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MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2304-2313
The Weighted Kendall and High-order Kernels for Permutations
Yunlong Jiao, Jean-Philippe Vert; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2314-2322
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin, Regina Barzilay, Tommi Jaakkola; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2323-2332
Network Global Testing by Counting Graphlets
Jiashun Jin, Zheng Ke, Shengming Luo; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2333-2341
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin, Kurt Keutzer, Sergey Levine; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2342-2351
WSNet: Compact and Efficient Networks Through Weight Sampling
Xiaojie Jin, Yingzhen Yang, Ning Xu, Jianchao Yang, Nebojsa Jojic, Jiashi Feng, Shuicheng Yan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2352-2361
Large-Scale Cox Process Inference using Variational Fourier Features
ST John, James Hensman; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2362-2370
Composite Functional Gradient Learning of Generative Adversarial Models
Rie Johnson, Tong Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2371-2379
Kronecker Recurrent Units
Cijo Jose, Moustapha Cisse, Francois Fleuret; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2380-2389
Fast Decoding in Sequence Models Using Discrete Latent Variables
Lukasz Kaiser, Samy Bengio, Aurko Roy, Ashish Vaswani, Niki Parmar, Jakob Uszkoreit, Noam Shazeer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2390-2399
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Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2400-2409
Efficient Neural Audio Synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aaron Oord, Sander Dieleman, Koray Kavukcuoglu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2410-2419
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Learning Diffusion using Hyperparameters
Dimitris Kalimeris, Yaron Singer, Karthik Subbian, Udi Weinsberg; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2420-2428
Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit
Sreejith Kallummil, Sheetal Kalyani; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2429-2438
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Nathan Kallus, Angela Zhou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2439-2448
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
Ashwin Kalyan, Stefan Lee, Anitha Kannan, Dhruv Batra; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2449-2458
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Semi-Supervised Learning via Compact Latent Space Clustering
Konstantinos Kamnitsas, Daniel Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2459-2468
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Policy Optimization with Demonstrations
Bingyi Kang, Zequn Jie, Jiashi Feng; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2469-2478
Improving Sign Random Projections With Additional Information
Keegan Kang, Weipin Wong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2479-2487
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Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
Ehsan Asadi Kangarshahi, Ya-Ping Hsieh, Mehmet Fatih Sahin, Volkan Cevher; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2488-2496
Continual Reinforcement Learning with Complex Synapses
Christos Kaplanis, Murray Shanahan, Claudia Clopath; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2497-2506
LaVAN: Localized and Visible Adversarial Noise
Danny Karmon, Daniel Zoran, Yoav Goldberg; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2507-2515
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Riemannian Stochastic Recursive Gradient Algorithm
Hiroyuki Kasai, Hiroyuki Sato, Bamdev Mishra; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2516-2524
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
Angelos Katharopoulos, Francois Fleuret; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2525-2534
Feasible Arm Identification
Julian Katz-Samuels, Clay Scott; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2535-2543
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints
Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2544-2553
Focused Hierarchical RNNs for Conditional Sequence Processing
Nan Rosemary Ke, Konrad Żołna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher Pal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2554-2563
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Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns, Seth Neel, Aaron Roth, Zhiwei Steven Wu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2564-2572
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Improved nearest neighbor search using auxiliary information and priority functions
Omid Keivani, Kaushik Sinha; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2573-2581
ContextNet: Deep learning for Star Galaxy Classification
Noble Kennamer, David Kirkby, Alexander Ihler, Francisco Javier Sanchez-Lopez; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2582-2590
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Frank-Wolfe with Subsampling Oracle
Thomas Kerdreux, Fabian Pedregosa, Alexandre d’Aspremont; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2591-2600
Convergence guarantees for a class of non-convex and non-smooth optimization problems
Koulik Khamaru, Martin Wainwright; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2601-2610
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2611-2620
Geometry Score: A Method For Comparing Generative Adversarial Networks
Valentin Khrulkov, Ivan Oseledets; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2621-2629
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Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus, Adria Gascon, Matt Kusner, Michael Veale, Krishna Gummadi, Adrian Weller; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2630-2639
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data
Minyoung Kim; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2640-2648
Disentangling by Factorising
Hyunjik Kim, Andriy Mnih; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2649-2658
Self-Bounded Prediction Suffix Tree via Approximate String Matching
Dongwoo Kim, Christian Walder; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2659-2667
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, Rory sayres; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2668-2677
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Semi-Amortized Variational Autoencoders
Yoon Kim, Sam Wiseman, Andrew Miller, David Sontag, Alexander Rush; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2678-2687
Neural Relational Inference for Interacting Systems
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard Zemel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2688-2697
An Alternative View: When Does SGD Escape Local Minima?
Bobby Kleinberg, Yuanzhi Li, Yang Yuan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2698-2707
Crowdsourcing with Arbitrary Adversaries
Matthaeus Kleindessner, Pranjal Awasthi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2708-2717
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
Jeremias Knoblauch, Theodoros Damoulas; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2718-2727
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani, Tamas Keviczky; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2728-2736
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Nonconvex Optimization for Regression with Fairness Constraints
Junpei Komiyama, Akiko Takeda, Junya Honda, Hajime Shimao; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2737-2746
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
Risi Kondor, Shubhendu Trivedi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2747-2755
Compiling Combinatorial Prediction Games
Frederic Koriche; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2756-2765
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Dynamic Evaluation of Neural Sequence Models
Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2766-2775
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Semiparametric Contextual Bandits
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2776-2785
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
Alan Kuhnle, J. David Smith, Victoria Crawford, My Thai; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2786-2795
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Volodymyr Kuleshov, Nathan Fenner, Stefano Ermon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2796-2804
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Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
Aviral Kumar, Sunita Sarawagi, Ujjwal Jain; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2805-2814
Data-Dependent Stability of Stochastic Gradient Descent
Ilja Kuzborskij, Christoph Lampert; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2815-2824
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong LI, Yves Grandvalet, Franck Davoine; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2825-2834
Understanding the Loss Surface of Neural Networks for Binary Classification
SHIYU LIANG, Ruoyu Sun, Yixuan Li, Rayadurgam Srikant; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2835-2843
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Mixed batches and symmetric discriminators for GAN training
Thomas LUCAS, Corentin Tallec, Yann Ollivier, Jakob Verbeek; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2844-2853
Binary Partitions with Approximate Minimum Impurity
Eduardo Laber, Marco Molinaro, Felipe Mello Pereira; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2854-2862
Canonical Tensor Decomposition for Knowledge Base Completion
Timothee Lacroix, Nicolas Usunier, Guillaume Obozinski; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2863-2872
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
Brenden Lake, Marco Baroni; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2873-2882
An Estimation and Analysis Framework for the Rasch Model
Andrew Lan, Mung Chiang, Christoph Studer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2883-2891
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Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering
Jan-Hendrik Lange, Andreas Karrenbauer, Bjoern Andres; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2892-2901
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global
Thomas Laurent, James Brecht; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2902-2907
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The Multilinear Structure of ReLU Networks
Thomas Laurent, James Brecht; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2908-2916
Hierarchical Imitation and Reinforcement Learning
Hoang Le, Nan Jiang, Alekh Agarwal, Miroslav Dudik, Yisong Yue, Hal Daumé III; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2917-2926
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
Yoonho Lee, Seungjin Choi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2927-2936
Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling
Kyowoon Lee, Sol-A Kim, Jaesik Choi, Seong-Whan Lee; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2937-2946
Gated Path Planning Networks
Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2947-2955
Deep Asymmetric Multi-task Feature Learning
Hae Beom Lee, Eunho Yang, Sung Ju Hwang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2956-2964
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, Timo Aila; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2965-2974
Out-of-sample extension of graph adjacency spectral embedding
Keith Levin, Fred Roosta, Michael Mahoney, Carey Priebe; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2975-2984
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An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks
Qianxiao Li, Shuji Hao; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2985-2994
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tieyan Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2995-3004
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On the Limitations of First-Order Approximation in GAN Dynamics
Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3005-3013
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
Pan Li, Olgica Milenkovic; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3014-3023
The Well-Tempered Lasso
Yuanzhi Li, Yoram Singer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3024-3032
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Estimation of Markov Chain via Rank-Constrained Likelihood
Xudong Li, Mengdi Wang, Anru Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3033-3042
Asynchronous Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3043-3052
RLlib: Abstractions for Distributed Reinforcement Learning
Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Ken Goldberg, Joseph Gonzalez, Michael Jordan, Ion Stoica; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3053-3062
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao, Romain Couillet; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3063-3071
The Dynamics of Learning: A Random Matrix Approach
Zhenyu Liao, Romain Couillet; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3072-3081
Reviving and Improving Recurrent Back-Propagation
Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard Zemel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3082-3091
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
Junhong Lin, Volkan Cevher; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3092-3101
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
Junhong Lin, Volkan Cevher; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3102-3111
Level-Set Methods for Finite-Sum Constrained Convex Optimization
Qihang Lin, Runchao Ma, Tianbao Yang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3112-3121
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary Lipton, Yu-Xiang Wang, Alexander Smola; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3122-3130
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
Haitao Liu, Jianfei Cai, Yi Wang, Yew Soon Ong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3131-3140
Towards Black-box Iterative Machine Teaching
Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James Rehg, Le Song; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3141-3149
Delayed Impact of Fair Machine Learning
Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3150-3158
A Two-Step Computation of the Exact GAN Wasserstein Distance
Huidong Liu, Xianfeng GU, Dimitris Samaras; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3159-3168
Open Category Detection with PAC Guarantees
Si Liu, Risheek Garrepalli, Thomas Dietterich, Alan Fern, Dan Hendrycks; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3169-3178
Fast Variance Reduction Method with Stochastic Batch Size
Xuanqing Liu, Cho-Jui Hsieh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3179-3188
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
Mingrui Liu, Xiaoxuan Zhang, Zaiyi Chen, Xiaoyu Wang, Tianbao Yang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3189-3197
On Matching Pursuit and Coordinate Descent
Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Raetsch, Bernhard Schölkopf, Sebastian Stich, Martin Jaggi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3198-3207
PDE-Net: Learning PDEs from Data
Zichao Long, Yiping Lu, Xianzhong Ma, Bin Dong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3208-3216
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
Miles Lopes, Shusen Wang, Michael Mahoney; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3217-3226
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Constraining the Dynamics of Deep Probabilistic Models
Marco Lorenzi, Maurizio Filippone; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3227-3236
Spectrally Approximating Large Graphs with Smaller Graphs
Andreas Loukas, Pierre Vandergheynst; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3237-3246
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3247-3256
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Accelerating Greedy Coordinate Descent Methods
Haihao Lu, Robert Freund, Vahab Mirrokni; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3257-3266
Structured Variationally Auto-encoded Optimization
Xiaoyu Lu, Javier Gonzalez, Zhenwen Dai, Neil D. Lawrence; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3267-3275
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
Yiping Lu, Aoxiao Zhong, Quanzheng Li, Bin Dong; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3276-3285
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End-to-end Active Object Tracking via Reinforcement Learning
Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3286-3295
Competitive Caching with Machine Learned Advice
Thodoris Lykouris, Sergei Vassilvtiskii; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3296-3305
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
Wenlong Lyu, Fan Yang, Changhao Yan, Dian Zhou, Xuan Zeng; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3306-3314
Celer: a Fast Solver for the Lasso with Dual Extrapolation
Mathurin MASSIAS, Alexandre Gramfort, Joseph Salmon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3315-3324
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
Siyuan Ma, Raef Bassily, Mikhail Belkin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3325-3334
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Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
Yao Ma, Alexander Olshevsky, Csaba Szepesvari, Venkatesh Saligrama; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3335-3344
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3345-3354
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah Erfani, Shutao Xia, Sudanthi Wijewickrema, James Bailey; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3355-3364
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Approximate message passing for amplitude based optimization
Junjie Ma, Ji Xu, Arian Maleki; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3365-3374
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3375-3383
Learning Adversarially Fair and Transferable Representations
David Madras, Elliot Creager, Toniann Pitassi, Richard Zemel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3384-3393
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Dhruv Malik, Malayandi Palaniappan, Jaime Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca Dragan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3394-3402
Iterative Amortized Inference
Joe Marino, Yisong Yue, Stephan Mandt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3403-3412
Streaming Principal Component Analysis in Noisy Setting
Teodor Vanislavov Marinov, Poorya Mianjy, Raman Arora; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3413-3422
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin, Andreas Loukas, Pierre Vandergheynst; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3423-3432
Bayesian Model Selection for Change Point Detection and Clustering
Othmane Mazhar, Cristian Rojas, Carlo Fischione, Mohammad Reza Hesamzadeh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3433-3442
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod, Stephen Roberts, Michael A. Osborne; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3443-3452
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Bounds on the Approximation Power of Feedforward Neural Networks
Mohammad Mehrabi, Aslan Tchamkerten, MANSOOR YOUSEFI; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3453-3461
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Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch, Mathieu Blondel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3462-3471
Ranking Distributions based on Noisy Sorting
Adil El Mesaoudi-Paul, Eyke Hüllermeier, Robert Busa-Fekete; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3472-3480
Which Training Methods for GANs do actually Converge?
Lars Mescheder, Andreas Geiger, Sebastian Nowozin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3481-3490
Configurable Markov Decision Processes
Alberto Maria Metelli, Mirco Mutti, Marcello Restelli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3491-3500
prDeep: Robust Phase Retrieval with a Flexible Deep Network
Christopher Metzler, Phillip Schniter, Ashok Veeraraghavan, Richard Baraniuk; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3501-3510
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Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back
Elliot Meyerson, Risto Miikkulainen; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3511-3520
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The Hidden Vulnerability of Distributed Learning in Byzantium
El-Mahdi El-Mhamdi, Rachid Guerraoui, Sébastien Rouault; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3521-3530
Stochastic PCA with $\ell_2$ and $\ell_1$ Regularization
Poorya Mianjy, Raman Arora; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3531-3539
On the Implicit Bias of Dropout
Poorya Mianjy, Raman Arora, Rene Vidal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3540-3548
One-Shot Segmentation in Clutter
Claudio Michaelis, Matthias Bethge, Alexander Ecker; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3549-3558
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Differentiable plasticity: training plastic neural networks with backpropagation
Thomas Miconi, Kenneth Stanley, Jeff Clune; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3559-3568
Training Neural Machines with Trace-Based Supervision
Matthew Mirman, Dimitar Dimitrov, Pavle Djordjevic, Timon Gehr, Martin Vechev; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3569-3577
Differentiable Abstract Interpretation for Provably Robust Neural Networks
Matthew Mirman, Timon Gehr, Martin Vechev; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3578-3586
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3587-3595
Data Summarization at Scale: A Two-Stage Submodular Approach
Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3596-3605
The Hierarchical Adaptive Forgetting Variational Filter
Vincent Moens; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3606-3615
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
Aryan Mokhtari, Hamed Hassani, Amin Karbasi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3616-3625
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
Thomas Moreau, Laurent Oudre, Nicolas Vayatis; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3626-3634
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
Marine Le Morvan, Jean-Philippe Vert; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3635-3644
Dropout Training, Data-dependent Regularization, and Generalization Bounds
Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3645-3653
Kernelized Synaptic Weight Matrices
Lorenz Muller, Julien Martel, Giacomo Indiveri; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3654-3663
Rapid Adaptation with Conditionally Shifted Neurons
Tsendsuren Munkhdalai, Xingdi Yuan, Soroush Mehri, Adam Trischler; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3664-3673
On the Relationship between Data Efficiency and Error for Uncertainty Sampling
Stephen Mussmann, Percy Liang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3674-3682
Fitting New Speakers Based on a Short Untranscribed Sample
Eliya Nachmani, Adam Polyak, Yaniv Taigman, Lior Wolf; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3683-3691
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Smoothed Action Value Functions for Learning Gaussian Policies
Ofir Nachum, Mohammad Norouzi, George Tucker, Dale Schuurmans; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3692-3700
Nearly Optimal Robust Subspace Tracking
Praneeth Narayanamurthy, Namrata Vaswani; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3701-3709
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Stochastic Proximal Algorithms for AUC Maximization
Michael Natole, Yiming Ying, Siwei Lyu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3710-3719
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Mitigating Bias in Adaptive Data Gathering via Differential Privacy
Seth Neel, Aaron Roth; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3720-3729
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Optimization Landscape and Expressivity of Deep CNNs
Quynh Nguyen, Matthias Hein; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3730-3739
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3740-3749
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
Lam Nguyen, PHUONG HA NGUYEN, Marten Dijk, Peter Richtarik, Katya Scheinberg, Martin Takac; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3750-3758
Active Testing: An Efficient and Robust Framework for Estimating Accuracy
Phuc Nguyen, Deva Ramanan, Charless Fowlkes; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3759-3768
On Learning Sparsely Used Dictionaries from Incomplete Samples
Thanh Nguyen, Akshay Soni, Chinmay Hegde; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3769-3778
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
Maximillian Nickel, Douwe Kiela; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3779-3788
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State Space Gaussian Processes with Non-Gaussian Likelihood
Hannes Nickisch, Arno Solin, Alexander Grigorevskiy; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3789-3798
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SparseMAP: Differentiable Sparse Structured Inference
Vlad Niculae, Andre Martins, Mathieu Blondel, Claire Cardie; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3799-3808
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
Weili Nie, Yang Zhang, Ankit Patel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3809-3818
Functional Gradient Boosting based on Residual Network Perception
Atsushi Nitanda, Taiji Suzuki; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3819-3828
Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams
Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovic, Amir Zandieh, Aidasadat Mousavifar, Ola Svensson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3829-3838
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The Uncertainty Bellman Equation and Exploration
Brendan O’Donoghue, Ian Osband, Remi Munos, Vlad Mnih; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3839-3848
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena, Jacob Buckman, Catherine Olsson, Tom Brown, Christopher Olah, Colin Raffel, Ian Goodfellow; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3849-3858
Learning in Reproducing Kernel Kreı̆n Spaces
Dino Oglic, Thomas Gaertner; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3859-3867
BOCK : Bayesian Optimization with Cylindrical Kernels
ChangYong Oh, Efstratios Gavves, Max Welling; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3868-3877
Self-Imitation Learning
Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3878-3887
A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks
Akifumi Okuno, Tetsuya Hada, Hidetoshi Shimodaira; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3888-3897
Transformation Autoregressive Networks
Junier Oliva, Avinava Dubey, Manzil Zaheer, Barnabas Poczos, Ruslan Salakhutdinov, Eric Xing, Jeff Schneider; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3898-3907
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches
Simon Olofsson, Marc Deisenroth, Ruth Misener; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3908-3917
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
Aaron Oord, Yazhe Li, Igor Babuschkin, Karen Simonyan, Oriol Vinyals, Koray Kavukcuoglu, George Driessche, Edward Lockhart, Luis Cobo, Florian Stimberg, Norman Casagrande, Dominik Grewe, Seb Noury, Sander Dieleman, Erich Elsen, Nal Kalchbrenner, Heiga Zen, Alex Graves, Helen King, Tom Walters, Dan Belov, Demis Hassabis; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3918-3926
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Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama, Dave Zachariah, Thomas Schön; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3927-3935
Autoregressive Quantile Networks for Generative Modeling
Georg Ostrovski, Will Dabney, Remi Munos; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3936-3945
Efficient First-Order Algorithms for Adaptive Signal Denoising
Dmitrii Ostrovskii, Zaid Harchaoui; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3946-3955
Analyzing Uncertainty in Neural Machine Translation
Myle Ott, Michael Auli, David Grangier, Marc’Aurelio Ranzato; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3956-3965
Learning Compact Neural Networks with Regularization
Samet Oymak; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3966-3975
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Tree Edit Distance Learning via Adaptive Symbol Embeddings
Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Barbara Hammer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3976-3985
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3986-3995
Learning to Speed Up Structured Output Prediction
Xingyuan Pan, Vivek Srikumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3996-4005
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
Xudong Pan, Mi Zhang, Daizong Ding; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4006-4015
Max-Mahalanobis Linear Discriminant Analysis Networks
Tianyu Pang, Chao Du, Jun Zhu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4016-4025
Stochastic Variance-Reduced Policy Gradient
Matteo Papini, Damiano Binaghi, Giuseppe Canonaco, Matteo Pirotta, Marcello Restelli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4026-4035
Learning Independent Causal Mechanisms
Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schölkopf; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4036-4044
Time Limits in Reinforcement Learning
Fabio Pardo, Arash Tavakoli, Vitaly Levdik, Petar Kormushev; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4045-4054
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Image Transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, Dustin Tran; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4055-4064
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PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
Paavo Parmas, Carl Edward Rasmussen, Jan Peters, Kenji Doya; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4065-4074
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High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
Tim Pearce, Alexandra Brintrup, Mohamed Zaki, Andy Neely; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4075-4084
Adaptive Three Operator Splitting
Fabian Pedregosa, Gauthier Gidel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4085-4094
Efficient Neural Architecture Search via Parameters Sharing
Hieu Pham, Melody Guan, Barret Zoph, Quoc Le, Jeff Dean; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4095-4104
Bandits with Delayed, Aggregated Anonymous Feedback
Ciara Pike-Burke, Shipra Agrawal, Csaba Szepesvari, Steffen Grunewalder; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4105-4113
Constant-Time Predictive Distributions for Gaussian Processes
Geoff Pleiss, Jacob Gardner, Kilian Weinberger, Andrew Gordon Wilson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4114-4123
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Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
Clarice Poon, Jingwei Liang, Carola Schoenlieb; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4124-4132
Equivalence of Multicategory SVM and Simplex Cone SVM: Fast Computations and Statistical Theory
Guillaume Pouliot; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4133-4140
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Learning Dynamics of Linear Denoising Autoencoders
Arnu Pretorius, Steve Kroon, Herman Kamper; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4141-4150
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin Duke; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4151-4160
Selecting Representative Examples for Program Synthesis
Yewen Pu, Zachery Miranda, Armando Solar-Lezama, Leslie Kaelbling; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4161-4170
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
Siyuan Qi, Baoxiong Jia, Song-Chun Zhu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4171-4179
Do Outliers Ruin Collaboration?
Mingda Qiao; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4180-4187
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Gradually Updated Neural Networks for Large-Scale Image Recognition
Siyuan Qiao, Zhishuai Zhang, Wei Shen, Bo Wang, Alan Yuille; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4188-4197
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
Qiang Qiu, Xiuyuan Cheng, Calderbank, Guillermo Sapiro; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4198-4207
Non-convex Conditional Gradient Sliding
Chao Qu, Yan Li, Huan Xu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4208-4217
Machine Theory of Mind
Neil Rabinowitz, Frank Perbet, Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4218-4227
Fast Parametric Learning with Activation Memorization
Jack Rae, Chris Dyer, Peter Dayan, Timothy Lillicrap; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4228-4237
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
Maithra Raghu, Alex Irpan, Jacob Andreas, Bobby Kleinberg, Quoc Le, Jon Kleinberg; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4238-4246
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
Hugo Raguet, Loic Landrieu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4247-4256
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Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4257-4266
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On Nesting Monte Carlo Estimators
Tom Rainforth, Rob Cornish, Hongseok Yang, Andrew Warrington, Frank Wood; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4267-4276
Tighter Variational Bounds are Not Necessarily Better
Tom Rainforth, Adam Kosiorek, Tuan Anh Le, Chris Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4277-4285
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
Aaditya Ramdas, Tijana Zrnic, Martin Wainwright, Michael Jordan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4286-4294
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, Shimon Whiteson; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4295-4304
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv, Rashish Tandon, Alex Dimakis, Itzhak Tamo; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4305-4313
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Learning Implicit Generative Models with the Method of Learned Moments
Suman Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4314-4323
Weightless: Lossy weight encoding for deep neural network compression
Brandon Reagan, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander Rush, Gu-Yeon Wei, David Brooks; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4324-4333
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4334-4343
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Learning by Playing Solving Sparse Reward Tasks from Scratch
Martin Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Wiele, Vlad Mnih, Nicolas Heess, Jost Tobias Springenberg; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4344-4353
Been There, Done That: Meta-Learning with Episodic Recall
Samuel Ritter, Jane Wang, Zeb Kurth-Nelson, Siddhant Jayakumar, Charles Blundell, Razvan Pascanu, Matthew Botvinick; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4354-4363
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A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
Adam Roberts, Jesse Engel, Colin Raffel, Curtis Hawthorne, Douglas Eck; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4364-4373
Learning to Optimize Combinatorial Functions
Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4374-4383
Fast Information-theoretic Bayesian Optimisation
Binxin Ru, Michael A. Osborne, Mark Mcleod, Diego Granziol; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4384-4392
Deep One-Class Classification
Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, Marius Kloft; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4393-4402
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
Francisco Ruiz, Michalis Titsias, Adji Bousso Dieng, David Blei; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4403-4412
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Probabilistic Boolean Tensor Decomposition
Tammo Rukat, Chris Holmes, Christopher Yau; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4413-4422
Black-Box Variational Inference for Stochastic Differential Equations
Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4423-4432
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Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Itay Safran, Ohad Shamir; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4433-4441
Learning Equations for Extrapolation and Control
Subham Sahoo, Christoph Lampert, Georg Martius; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4442-4450
Tempered Adversarial Networks
Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schölkopf; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4451-4459
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Representation Tradeoffs for Hyperbolic Embeddings
Frederic Sala, Chris De Sa, Albert Gu, Christopher Re; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4460-4469
Graph Networks as Learnable Physics Engines for Inference and Control
Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin Riedmiller, Raia Hadsell, Peter Battaglia; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4470-4479
A Classification-Based Study of Covariate Shift in GAN Distributions
Shibani Santurkar, Ludwig Schmidt, Aleksander Madry; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4480-4489
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Amartya Sanyal, Matt Kusner, Adria Gascon, Varun Kanade; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4490-4499
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Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4500-4508
Learning with Abandonment
Sven Schmit, Ramesh Johari; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4509-4517
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab, Emanuela Keller, Carl Muroi, David J. Mack, Christian Strässle, Walter Karlen; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4518-4527
Progress & Compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4528-4537
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4538-4547
Overcoming Catastrophic Forgetting with Hard Attention to the Task
Joan Serra, Didac Suris, Marius Miron, Alexandros Karatzoglou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4548-4557
Bounding and Counting Linear Regions of Deep Neural Networks
Thiago Serra, Christian Tjandraatmadja, Srikumar Ramalingam; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4558-4566
First Order Generative Adversarial Networks
Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4567-4576
Finding Influential Training Samples for Gradient Boosted Decision Trees
Boris Sharchilev, Yury Ustinovskiy, Pavel Serdyukov, Maarten Rijke; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4577-4585
Solving Partial Assignment Problems using Random Clique Complexes
Charu Sharma, Deepak Nathani, Manohar Kaul; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4586-4595
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Noam Shazeer, Mitchell Stern; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4596-4604
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Locally Private Hypothesis Testing
Or Sheffet; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4605-4614
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
Daniel Sheldon, Kevin Winner, Debora Sujono; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4615-4623
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4624-4633
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
Li Shen, Peng Sun, Yitong Wang, Wei Liu, Tong Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4634-4643
A Spectral Approach to Gradient Estimation for Implicit Distributions
Jiaxin Shi, Shengyang Sun, Jun Zhu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4644-4653
TACO: Learning Task Decomposition via Temporal Alignment for Control
Kyriacos Shiarlis, Markus Wulfmeier, Sasha Salter, Shimon Whiteson, Ingmar Posner; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4654-4663
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
Wissam Siblini, Pascale Kuntz, Frank Meyer; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4664-4673
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Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
Umut Simsekli, Cagatay Yildiz, Than Huy Nguyen, Taylan Cemgil, Gael Richard; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4674-4683
K-means clustering using random matrix sparsification
Kaushik Sinha; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4684-4692
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
RJ Skerry-Ryan, Eric Battenberg, Ying Xiao, Yuxuan Wang, Daisy Stanton, Joel Shor, Ron Weiss, Rob Clark, Rif A. Saurous; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4693-4702
An Inference-Based Policy Gradient Method for Learning Options
Matthew Smith, Herke Hoof, Joelle Pineau; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4703-4712
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Accelerating Natural Gradient with Higher-Order Invariance
Yang Song, Jiaming Song, Stefano Ermon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4713-4722
Knowledge Transfer with Jacobian Matching
Suraj Srinivas, Francois Fleuret; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4723-4731
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control
Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4732-4741
Structured Control Nets for Deep Reinforcement Learning
Mario Srouji, Jian Zhang, Ruslan Salakhutdinov; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4742-4751
Approximation Algorithms for Cascading Prediction Models
Matthew Streeter; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4752-4760
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Learning Low-Dimensional Temporal Representations
Bing Su, Ying Wu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4761-4770
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
Masanori Suganuma, Mete Ozay, Takayuki Okatani; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4771-4780
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Stagewise Safe Bayesian Optimization with Gaussian Processes
Yanan Sui, Vincent Zhuang, Joel Burdick, Yisong Yue; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4781-4789
Neural Program Synthesis from Diverse Demonstration Videos
Shao-Hua Sun, Hyeonwoo Noh, Sriram Somasundaram, Joseph Lim; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4790-4799
Scalable approximate Bayesian inference for particle tracking data
Ruoxi Sun, Liam Paninski; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4800-4809
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4810-4817
Convolutional Imputation of Matrix Networks
Qingyun Sun, Mengyuan Yan, David Donoho, boyd; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4818-4827
Differentiable Compositional Kernel Learning for Gaussian Processes
Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger Grosse; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4828-4837
Learning the Reward Function for a Misspecified Model
Erik Talvitie; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4838-4847
$D^2$: Decentralized Training over Decentralized Data
Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4848-4856
Neural Inverse Rendering for General Reflectance Photometric Stereo
Tatsunori Taniai, Takanori Maehara; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4857-4866
Black Box FDR
Wesley Tansey, Yixin Wang, David Blei, Raul Rabadan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4867-4876
Best Arm Identification in Linear Bandits with Linear Dimension Dependency
Chao Tao, Saúl Blanco, Yuan Zhou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4877-4886
Chi-square Generative Adversarial Network
Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin Duke; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4887-4896
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees
Adrien Taylor, Bryan Van Scoy, Laurent Lessard; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4897-4906
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Mattias Teye, Hossein Azizpour, Kevin Smith; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4907-4916
Decoupling Gradient-Like Learning Rules from Representations
Philip Thomas, Christoph Dann, Emma Brunskill; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4917-4925
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
Kevin Tian, Teng Zhang, James Zou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4926-4935
Importance Weighted Transfer of Samples in Reinforcement Learning
Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4936-4945
Adversarial Regression with Multiple Learners
Liang Tong, Sixie Yu, Scott Alfeld, vorobeychik; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4946-4954
Convergent Tree Backup and Retrace with Function Approximation
Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4955-4964
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Trieu Trinh, Andrew Dai, Thang Luong, Quoc Le; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4965-4974
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Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Manolis Tsakiris, Rene Vidal; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4975-4984
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StrassenNets: Deep Learning with a Multiplication Budget
Michael Tschannen, Aran Khanna, Animashree Anandkumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4985-4994
Invariance of Weight Distributions in Rectified MLPs
Russell Tsuchida, Fred Roosta, Marcus Gallagher; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4995-5004
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
Stephen Tu, Benjamin Recht; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5005-5014
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The Mirage of Action-Dependent Baselines in Reinforcement Learning
George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard Turner, Zoubin Ghahramani, Sergey Levine; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5015-5024
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Jonathan Uesato, Brendan O’Donoghue, Pushmeet Kohli, Aaron Oord; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5025-5034
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
Arash Vahdat, William Macready, Zhengbing Bian, Amir Khoshaman, Evgeny Andriyash; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5035-5044
Programmatically Interpretable Reinforcement Learning
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5045-5054
Clustering Semi-Random Mixtures of Gaussians
Aravindan Vijayaraghavan, Pranjal Awasthi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5055-5064
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
Robin Vogel, Aurélien Bellet, Stéphan Clémençon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5065-5074
Hierarchical Multi-Label Classification Networks
Jonatas Wehrmann, Ricardo Cerri, Rodrigo Barros; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5075-5084
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Transfer Learning via Learning to Transfer
Ying WEI, Yu Zhang, Junzhou Huang, Qiang Yang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5085-5094
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
Tal Wagner, Sudipto Guha, Shiva Kasiviswanathan, Nina Mishra; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5095-5104
Neural Dynamic Programming for Musical Self Similarity
Christian Walder, Dongwoo Kim; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5105-5113
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Thompson Sampling for Combinatorial Semi-Bandits
Siwei Wang, Wei Chen; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5114-5122
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S Yu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5123-5132
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Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang, Somesh Jha, Kamalika Chaudhuri; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5133-5142
Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations
Xingyu Wang, Diego Klabjan; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5143-5151
Coded Sparse Matrix Multiplication
Sinong Wang, Jiashang Liu, Ness Shroff; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5152-5160
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
Beilun Wang, Arshdeep Sekhon, Yanjun Qi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5161-5170
Provable Variable Selection for Streaming Features
Jing Wang, Jie Shen, Ping Li; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5171-5179
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Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
Yuxuan Wang, Daisy Stanton, Yu Zhang, RJ-Skerry Ryan, Eric Battenberg, Joel Shor, Ying Xiao, Ye Jia, Fei Ren, Rif A. Saurous; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5180-5189
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Adversarial Distillation of Bayesian Neural Network Posteriors
Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger Grosse, Richard Zemel; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5190-5199
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Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
Xue Wang, Mingcheng Wei, Tao Yao; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5200-5208
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
Yaqing Wang, Quanming Yao, James Tin-Yau Kwok, Lionel M. NI; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5209-5218
Stein Variational Message Passing for Continuous Graphical Models
Dilin Wang, Zhe Zeng, Qiang Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5219-5227
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab Mirrokni; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5228-5237
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
Daphna Weinshall, Gad Cohen, Dan Amir; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5238-5246
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Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss, Yoav Goldberg, Eran Yahav; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5247-5256
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
Gellert Weisz, Andras Gyorgy, Csaba Szepesvari; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5257-5265
Deep Predictive Coding Network for Object Recognition
Haiguang Wen, Kuan Han, Junxing Shi, Yizhen Zhang, Eugenio Culurciello, Zhongming Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5266-5275
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Towards Fast Computation of Certified Robustness for ReLU Networks
Lily Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane Boning, Inderjit Dhillon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5276-5285
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope
Eric Wong, Zico Kolter; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5286-5295
Local Density Estimation in High Dimensions
Xian Wu, Moses Charikar, Vishnu Natchu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5296-5305
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
Huasen Wu, Xueying Guo, Xin Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5306-5314
SQL-Rank: A Listwise Approach to Collaborative Ranking
Liwei Wu, Cho-Jui Hsieh, James Sharpnack; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5315-5324
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5325-5333
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5334-5342
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Yi Wu, Siddharth Srivastava, Nicholas Hay, Simon Du, Stuart Russell; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5343-5352
Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization
Hang Wu, May Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5353-5362
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5363-5372
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Bayesian Quadrature for Multiple Related Integrals
Xiaoyue Xi, Francois-Xavier Briol, Mark Girolami; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5373-5382
Model-Level Dual Learning
Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5383-5392
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao, Yasaman Bahri, Jascha Sohl-Dickstein, Samuel Schoenholz, Jeffrey Pennington; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5393-5402
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
Pengtao Xie, Wei Wu, Yichen Zhu, Eric Xing; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5403-5412
Nonoverlap-Promoting Variable Selection
Pengtao Xie, Hongbao Zhang, Yichen Zhu, Eric Xing; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5413-5422
Learning Semantic Representations for Unsupervised Domain Adaptation
Shaoan Xie, Zibin Zheng, Liang Chen, Chuan Chen; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5423-5432
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Rates of Convergence of Spectral Methods for Graphon Estimation
Jiaming Xu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5433-5442
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Learning Registered Point Processes from Idiosyncratic Observations
Hongteng Xu, Lawrence Carin, Hongyuan Zha; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5443-5452
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5453-5462
Learning to Explore via Meta-Policy Gradient
Tianbing Xu, Qiang Liu, Liang Zhao, Jian Peng; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5463-5472
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Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5473-5482
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data
Ganggang Xu, Zuofeng Shang, Guang Cheng; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5483-5491
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
Pan Xu, Tianhao Wang, Quanquan Gu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5492-5501
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
Jingyi Xu, Zilu Zhang, Tal Friedman, Yitao Liang, Guy Broeck; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5502-5511
Causal Bandits with Propagating Inference
Akihiro Yabe, Daisuke Hatano, Hanna Sumita, Shinji Ito, Naonori Kakimura, Takuro Fukunaga, Ken-ichi Kawarabayashi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5512-5520
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Active Learning with Logged Data
Songbai Yan, Kamalika Chaudhuri, Tara Javidi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5521-5530
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Bowei Yan, Sanmi Koyejo, Kai Zhong, Pradeep Ravikumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5531-5540
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
Karren Yang, Abigail Katcoff, Caroline Uhler; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5541-5550
Dependent Relational Gamma Process Models for Longitudinal Networks
Sikun Yang, Heinz Koeppl; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5551-5560
Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy
Jiasen Yang, Qiang Liu, Vinayak Rao, Jennifer Neville; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5561-5570
Mean Field Multi-Agent Reinforcement Learning
Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, Jun Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5571-5580
Yes, but Did It Work?: Evaluating Variational Inference
Yuling Yao, Aki Vehtari, Daniel Simpson, Andrew Gelman; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5581-5590
Hierarchical Text Generation and Planning for Strategic Dialogue
Denis Yarats, Mike Lewis; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5591-5599
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Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
Grigory Yaroslavtsev, Adithya Vadapalli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5600-5609
Communication-Computation Efficient Gradient Coding
Min Ye, Emmanuel Abbe; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5610-5619
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Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach
Mao Ye, Yan Sun; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5620-5629
Loss Decomposition for Fast Learning in Large Output Spaces
Ian En-Hsu Yen, Satyen Kale, Felix Yu, Daniel Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5640-5649
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Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin, Yudong Chen, Ramchandran Kannan, Peter Bartlett; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5650-5659
Semi-Implicit Variational Inference
Mingzhang Yin, Mingyuan Zhou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5660-5669
Disentangled Sequential Autoencoder
Li Yingzhen, Stephan Mandt; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5670-5679
Probably Approximately Metric-Fair Learning
Gal Yona, Guy Rothblum; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5680-5688
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon, James Jordon, Mihaela Schaar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5689-5698
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
Jinsung Yoon, James Jordon, Mihaela Schaar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5699-5707
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan You, Rex Ying, Xiang Ren, William Hamilton, Jure Leskovec; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5708-5717
An Efficient Semismooth Newton based Algorithm for Convex Clustering
Yancheng Yuan, Defeng Sun, Kim-Chuan Toh; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5718-5726
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
Alp Yurtsever, Olivier Fercoq, Francesco Locatello, Volkan Cevher; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5727-5736
Policy Optimization as Wasserstein Gradient Flows
Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5737-5746
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
Andrea Zanette, Emma Brunskill; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5747-5755
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
Xiao Zhang, Simon Du, Quanquan Gu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5756-5765
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang, Salar Fattahi, Somayeh Sojoudi; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5766-5775
High Performance Zero-Memory Overhead Direct Convolutions
Jiyuan Zhang, Franz Franchetti, Tze Meng Low; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5776-5785
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Safe Element Screening for Submodular Function Minimization
Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, Tong Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5786-5795
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5796-5805
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Jiong Zhang, Qi Lei, Inderjit Dhillon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5806-5814
Learning Long Term Dependencies via Fourier Recurrent Units
Jiong Zhang, Yibo Lin, Zhao Song, Inderjit Dhillon; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5815-5823
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Tropical Geometry of Deep Neural Networks
Liwen Zhang, Gregory Naitzat, Lek-Heng Lim; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5824-5832
Deep Bayesian Nonparametric Tracking
Aonan Zhang, John Paisley; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5833-5841
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Composable Planning with Attributes
Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5842-5851
Noisy Natural Gradient as Variational Inference
Guodong Zhang, Shengyang Sun, David Duvenaud, Roger Grosse; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5852-5861
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
Xiao Zhang, Lingxiao Wang, Yaodong Yu, Quanquan Gu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5862-5871
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5872-5881
Dynamic Regret of Strongly Adaptive Methods
Lijun Zhang, Tianbao Yang, jin, Zhi-Hua Zhou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5882-5891
Inter and Intra Topic Structure Learning with Word Embeddings
He Zhao, Lan Du, Wray Buntine, Mingyuan Zhou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5892-5901
Adversarially Regularized Autoencoders
Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander Rush, Yann LeCun; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5902-5911
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
Bo Zhao, Xinwei Sun, Yanwei Fu, Yuan Yao, Yizhou Wang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5912-5921
Composite Marginal Likelihood Methods for Random Utility Models
Zhibing Zhao, Lirong Xia; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5922-5931
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data
Shuai Zheng, James Tin-Yau Kwok; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5932-5940
A Robust Approach to Sequential Information Theoretic Planning
Sue Zheng, Jason Pacheco, John Fisher; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5941-5949
Revealing Common Statistical Behaviors in Heterogeneous Populations
Andrey Zhitnikov, Rotem Mulayoff, Tomer Michaeli; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5950-5959
Understanding Generalization and Optimization Performance of Deep CNNs
Pan Zhou, Jiashi Feng; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5960-5969
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5970-5979
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates
Kaiwen Zhou, Fanhua Shang, James Cheng; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5980-5989
Stochastic Variance-Reduced Cubic Regularized Newton Methods
Dongruo Zhou, Pan Xu, Quanquan Gu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5990-5999
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
Yichi Zhou, Jun Zhu, Jingwei Zhuo; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:6000-6008
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Distributed Nonparametric Regression under Communication Constraints
Yuancheng Zhu, John Lafferty; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:6009-6017
Message Passing Stein Variational Gradient Descent
Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:6018-6027
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
Difan Zou, Pan Xu, Quanquan Gu; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:6028-6037
Rectify Heterogeneous Models with Semantic Mapping
Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5630-5639
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Hierarchical Long-term Video Prediction without Supervision
Nevan wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee; Proceedings of the 35th International Conference on Machine Learning, PMLR 80:6038-6046
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