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Editors: Arindam Banerjee, Kenji Fukumizu
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On the Effect of Auxiliary Tasks on Representation Dynamics
; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1-9
LassoNet: Neural Networks with Feature Sparsity
Ismael Lemhadri, Feng Ruan, Rob Tibshirani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:10-18
Projection-Free Optimization on Uniformly Convex Sets
Thomas Kerdreux, Alexandre d’Aspremont, Sebastian Pokutta; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:19-27
Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications
Shinsaku Sakaue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:28-36
Graphical Normalizing Flows
Antoine Wehenkel, Gilles Louppe; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:37-45
One-Round Communication Efficient Distributed M-Estimation
Yajie Bao, Weijia Xiong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:46-54
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices
Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:55-63
Regularized Policies are Reward Robust
Hisham Husain, Kamil Ciosek, Ryota Tomioka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:64-72
Semi-Supervised Learning with Meta-Gradient
Taihong Xiao, Xin-Yu Zhang, Haolin Jia, Ming-Ming Cheng, Ming-Hsuan Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:73-81
On Information Gain and Regret Bounds in Gaussian Process Bandits
Sattar Vakili, Kia Khezeli, Victor Picheny; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:82-90
On the proliferation of support vectors in high dimensions
Daniel Hsu, Vidya Muthukumar, Ji Xu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:91-99
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors
Nikhil Mehta, Kevin Liang, Vinay Kumar Verma, Lawrence Carin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:100-108
A Fast and Robust Method for Global Topological Functional Optimization
Yitzchak Solomon, Alexander Wagner, Paul Bendich; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:109-117
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Regression Discontinuity Design under Self-selection
Sida Peng, Yang Ning; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:118-126
Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns
Ziping Xu, Amirhossein Meisami, Ambuj Tewari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:127-135
When OT meets MoM: Robust estimation of Wasserstein Distance
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d’Alché-Buc; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:136-144
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint
Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:145-153
Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability
Naoto Ohsaka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:154-162
False Discovery Rates in Biological Networks
Lu Yu, Tobias Kaufmann, Johannes Lederer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:163-171
Fourier Bases for Solving Permutation Puzzles
Horace Pan, Risi Kondor; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:172-180
Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Feynman Liang, Nimar Arora, Nazanin Tehrani, Yucen Li, Michael Tingley, Erik Meijer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:181-189
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Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
Xing Han, Sambarta Dasgupta, Joydeep Ghosh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:190-198
Fully Gap-Dependent Bounds for Multinomial Logit Bandit
Jiaqi Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:199-207
Alternating Direction Method of Multipliers for Quantization
Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:208-216
Online Forgetting Process for Linear Regression Models
Yuantong Li, Chi-Hua Wang, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:217-225
A Bayesian nonparametric approach to count-min sketch under power-law data streams
Emanuele Dolera, Stefano Favaro, Stefano Peluchetti; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:226-234
Nonlinear Functional Output Regression: A Dictionary Approach
Dimitri Bouche, Marianne Clausel, François Roueff, Florence d’Alché-Buc; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:235-243
When MAML Can Adapt Fast and How to Assist When It Cannot
Sébastien Arnold, Shariq Iqbal, Fei Sha; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:244-252
Learning Smooth and Fair Representations
Xavier Gitiaux, Huzefa Rangwala; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:253-261
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
Tianyi Lin, Zeyu Zheng, Elynn Chen, Marco Cuturi, Michael I. Jordan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:262-270
Contextual Blocking Bandits
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:271-279
Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:280-288
A comparative study on sampling with replacement vs Poisson sampling in optimal subsampling
HaiYing Wang, Jiahui Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:289-297
Robust Imitation Learning from Noisy Demonstrations
Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:298-306
Online Active Model Selection for Pre-trained Classifiers
Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlaš, Johannes Rausch, Ce Zhang, Andreas Krause; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:307-315
Online Sparse Reinforcement Learning
Botao Hao, Tor Lattimore, Csaba Szepesvari, Mengdi Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:316-324
A Contraction Approach to Model-based Reinforcement Learning
Ting-Han Fan, Peter Ramadge; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:325-333
The Spectrum of Fisher Information of Deep Networks Achieving Dynamical Isometry
Tomohiro Hayase, Ryo Karakida; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:334-342
Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann, Jan Boelts, David Greenberg, Pedro Goncalves, Jakob Macke; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:343-351
Fisher Auto-Encoders
Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:352-360
Deep Spectral Ranking
Ilkay Yildiz, Jennifer Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:361-369
Tight Regret Bounds for Infinite-armed Linear Contextual Bandits
Yingkai Li, Yining Wang, Xi Chen, Yuan Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:370-378
On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems
Yingjie Bi, Javad Lavaei; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:379-387
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:388-396
Approximate Message Passing with Spectral Initialization for Generalized Linear Models
Marco Mondelli, Ramji Venkataramanan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:397-405
Active Learning with Maximum Margin Sparse Gaussian Processes
Weishi Shi, Qi Yu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:406-414
A Stein Goodness-of-test for Exponential Random Graph Models
Wenkai Xu, Gesine Reinert; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:415-423
The Sample Complexity of Level Set Approximation
François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:424-432
Curriculum Learning by Optimizing Learning Dynamics
Tianyi Zhou, Shengjie Wang, Jeff Bilmes; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:433-441
Approximating Lipschitz continuous functions with GroupSort neural networks
Ugo Tanielian, Gerard Biau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:442-450
Learning GPLVM with arbitrary kernels using the unscented transformation
Daniel de Souza, Diego Mesquita, João Paulo Gomes, César Lincoln Mattos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:451-459
Low-Rank Generalized Linear Bandit Problems
Yangyi Lu, Amirhossein Meisami, Ambuj Tewari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:460-468
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
Kai Brügge, Asja Fischer, Christian Igel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:469-477
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Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
Manuel Haußmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:478-486
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm
Majid Jahani, MohammadReza Nazari, Rachael Tappenden, Albert Berahas, Martin Takac; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:487-495
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
Yue Xing, Qifan Song, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:496-504
On the Generalization Properties of Adversarial Training
Yue Xing, Qifan Song, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:505-513
Adversarially Robust Estimate and Risk Analysis in Linear Regression
Yue Xing, Ruizhi Zhang, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:514-522
Adaptive Approximate Policy Iteration
Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:523-531
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
Guillaume Ausset, Stephan Clémencon, François Portier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:532-540
Foundations of Bayesian Learning from Synthetic Data
Harrison Wilde, Jack Jewson, Sebastian Vollmer, Chris Holmes; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:541-549
Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates
Damien Scieur, Lewis Liu, Thomas Pumir, Nicolas Boumal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:550-558
Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering
Danny Vainstein, Vaggos Chatziafratis, Gui Citovsky, Anand Rajagopalan, Mohammad Mahdian, Yossi Azar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:559-567
Generalization Bounds for Stochastic Saddle Point Problems
Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:568-576
Learning to Defend by Learning to Attack
Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:577-585
A Deterministic Streaming Sketch for Ridge Regression
Benwei Shi, Jeff Phillips; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:586-594
Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems
Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:595-603
On the Role of Data in PAC-Bayes Bounds
Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel Roy; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:604-612
CADA: Communication-Adaptive Distributed Adam
Tianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:613-621
Bandit algorithms: Letting go of logarithmic regret for statistical robustness
Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna Jagannathan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:622-630
Geometrically Enriched Latent Spaces
Georgios Arvanitidis, Soren Hauberg, Bernhard Schölkopf; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:631-639
Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting
Ilja Kuzborskij, Claire Vernade, Andras Gyorgy, Csaba Szepesvari; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:640-648
Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu, Zhenyu Liao, Johan Suykens; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:649-657
Self-Concordant Analysis of Generalized Linear Bandits with Forgetting
Yoan Russac, Louis Faury, Olivier Cappé, Aurélien Garivier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:658-666
Logical Team Q-learning: An approach towards factored policies in cooperative MARL
Lucas Cassano, Ali H. Sayed; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:667-675
Automatic structured variational inference
Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:676-684
Neural Enhanced Belief Propagation on Factor Graphs
Víctor Garcia Satorras, Max Welling; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:685-693
[abs][Download PDF]
Predictive Complexity Priors
Eric Nalisnick, Jonathan Gordon, Jose Miguel Hernandez-Lobato; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:694-702
Improving predictions of Bayesian neural nets via local linearization
Alexander Immer, Maciej Korzepa, Matthias Bauer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:703-711
Generalized Spectral Clustering via Gromov-Wasserstein Learning
Samir Chowdhury, Tom Needham; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:712-720
Shapley Flow: A Graph-based Approach to Interpreting Model Predictions
Jiaxuan Wang, Jenna Wiens, Scott Lundberg; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:721-729
Scalable Constrained Bayesian Optimization
David Eriksson, Matthias Poloczek; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:730-738
Sample efficient learning of image-based diagnostic classifiers via probabilistic labels
Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth, Jeevesh Kapur, Jacob Jaremko, Russell Greiner; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:739-747
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Nonparametric Variable Screening with Optimal Decision Stumps
Jason Klusowski, Peter Tian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:748-756
Sharp Analysis of a Simple Model for Random Forests
Jason Klusowski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:757-765
Nested Barycentric Coordinate System as an Explicit Feature Map
Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:766-774
An Analysis of the Adaptation Speed of Causal Models
Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:775-783
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
Robin Vogel, Aurélien Bellet, Stephan Clémençon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:784-792
Efficient Computation and Analysis of Distributional Shapley Values
Yongchan Kwon, Manuel A. Rivas, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:793-801
A constrained risk inequality for general losses
John Duchi, Feng Ruan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:802-810
[abs][Download PDF]
Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms
Tengyu Xu, Yingbin Liang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:811-819
Learning Prediction Intervals for Regression: Generalization and Calibration
Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:820-828
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
Tianyang Hu, Wenjia Wang, Cong Lin, Guang Cheng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:829-837
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, Yu-Xiang Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:838-846
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:847-855
Deep Fourier Kernel for Self-Attentive Point Processes
Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:856-864
Robustness and scalability under heavy tails, without strong convexity
Matthew Holland; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:865-873
Understanding the wiring evolution in differentiable neural architecture search
Sirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:874-882
Provable Hierarchical Imitation Learning via EM
Zhiyu Zhang, Ioannis Paschalidis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:883-891
Learning with risk-averse feedback under potentially heavy tails
Matthew Holland, El Mehdi Haress; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:892-900
Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy, Ichiro Takeuchi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:901-909
On the High Accuracy Limitation of Adaptive Property Estimation
Yanjun Han; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:910-918
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:919-927
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model
Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed Chi, Qiaozhu Mei; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:928-936
Interpretable Random Forests via Rule Extraction
Clément Bénard, Gérard Biau, Sébastien da Veiga, Erwan Scornet; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:937-945
Regret Minimization for Causal Inference on Large Treatment Space
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:946-954
Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions
Shunsuke Horii; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:955-963
Adaptive Sampling for Fast Constrained Maximization of Submodular Functions
Francesco Quinzan, Vanja Doskoc, Andreas Göbel, Tobias Friedrich; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:964-972
[abs][Download PDF]
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:973-981
Hadamard Wirtinger Flow for Sparse Phase Retrieval
Fan Wu, Patrick Rebeschini; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:982-990
Stochastic Linear Bandits Robust to Adversarial Attacks
Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:991-999
[abs][Download PDF]
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
Martin Royer, Frederic Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1000-1008
Optimizing Percentile Criterion using Robust MDPs
Bahram Behzadian, Reazul Hasan Russel, Marek Petrik, Chin Pang Ho; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1009-1017
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
Alain Durmus, Pablo Jiménez, Eric Moulines, Salem SAID; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1018-1026
Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy
Onur Teymur, Jackson Gorham, Marina Riabiz, Chris Oates; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1027-1035
Aligning Time Series on Incomparable Spaces
Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Deisenroth; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1036-1044
The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers
Mohamed El Amine Seddik, Cosme Louart, Romain COUILLET, Mohamed Tamaazousti; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1045-1053
Measure Transport with Kernel Stein Discrepancy
Matthew Fisher, Tui Nolan, Matthew Graham, Dennis Prangle, Chris Oates; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1054-1062
Unifying Clustered and Non-stationary Bandits
Chuanhao Li, Qingyun Wu, Hongning Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1063-1071
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1072-1080
Transforming Gaussian Processes With Normalizing Flows
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1081-1089
Linearly Constrained Gaussian Processes with Boundary Conditions
Markus Lange-Hegermann; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1090-1098
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings
Jean-Francois Ton, Lucian CHAN, Yee Whye Teh, Dino Sejdinovic; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1099-1107
Top-m identification for linear bandits
Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1108-1116
When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
Ziwei Guan, Tengyu Xu, Yingbin Liang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1117-1125
Online k-means Clustering
Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1126-1134
Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1135-1143
Algorithms for Fairness in Sequential Decision Making
Min Wen, Osbert Bastani, Ufuk Topcu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1144-1152
On Learning Continuous Pairwise Markov Random Fields
Abhin Shah, Devavrat Shah, Gregory Wornell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1153-1161
Abstract Value Iteration for Hierarchical Reinforcement Learning
Kishor Jothimurugan, Osbert Bastani, Rajeev Alur; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1162-1170
Differentially Private Analysis on Graph Streams
Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1171-1179
Learning with Hyperspherical Uniformity
Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1180-1188
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function
Ioannis Tsaknakis, Mingyi Hong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1189-1197
Latent Derivative Bayesian Last Layer Networks
Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1198-1206
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes
Nhuong Nguyen, Toan Nguyen, PHUONG HA NGUYEN, Quoc Tran-Dinh, Lam Nguyen, Marten van Dijk; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1207-1215
Provably Safe PAC-MDP Exploration Using Analogies
Melrose Roderick, Vaishnavh Nagarajan, Zico Kolter; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1216-1224
Maximal Couplings of the Metropolis-Hastings Algorithm
Guanyang Wang, John O’Leary, Pierre Jacob; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1225-1233
Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
Yahav Bechavod, Katrina Ligett, Steven Wu, Juba Ziani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1234-1242
Goodness-of-Fit Test for Mismatched Self-Exciting Processes
Song Wei, Shixiang Zhu, Minghe Zhang, Yao Xie; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1243-1251
Dominate or Delete: Decentralized Competing Bandits in Serial Dictatorship
Abishek Sankararaman, Soumya Basu, Karthik Abinav Sankararaman; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1252-1260
A Study of Condition Numbers for First-Order Optimization
Charles Guille-Escuret, Manuela Girotti, Baptiste Goujaud, Ioannis Mitliagkas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1261-1269
Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1270-1278
Differentially Private Online Submodular Maximization
Sebastian Perez Salazar, Rachel Cummings; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1279-1287
Anderson acceleration of coordinate descent
Quentin Bertrand, Mathurin Massias; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1288-1296
Inference in Stochastic Epidemic Models via Multinomial Approximations
Nick Whiteley, Lorenzo Rimella; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1297-1305
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence
Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1306-1314
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation
Robert Gower, Othmane Sebbouh, Nicolas Loizou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1315-1323
Stable ResNet
Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1324-1332
Latent variable modeling with random features
Gregory Gundersen, Michael Zhang, Barbara Engelhardt; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1333-1341
Reaping the Benefits of Bundling under High Production Costs
Will Ma, David Simchi-Levi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1342-1350
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Momentum Improves Optimization on Riemannian Manifolds
Foivos Alimisis, Antonio Orvieto, Gary Becigneul, Aurelien Lucchi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1351-1359
Quick Streaming Algorithms for Maximization of Monotone Submodular Functions in Linear Time
Alan Kuhnle; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1360-1368
On Data Efficiency of Meta-learning
Maruan Al-Shedivat, Liam Li, Eric Xing, Ameet Talwalkar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1369-1377
Hyperparameter Transfer Learning with Adaptive Complexity
Samuel Horváth, Aaron Klein, Peter Richtarik, Cedric Archambeau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1378-1386
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency
Yuyang Deng, Mehrdad Mahdavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1387-1395
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
Avishek Ghosh, Abishek Sankararaman, Ramchandran Kannan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1396-1404
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1405-1413
Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification
Zhuo Sun, Jijie Wu, Xiaoxu Li, Wenming Yang, Jing-Hao Xue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1414-1422
Tractable contextual bandits beyond realizability
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1423-1431
Learning User Preferences in Non-Stationary Environments
Wasim Huleihel, Soumyabrata Pal, Ofer Shayevitz; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1432-1440
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes
Qi Lei, Sai Ganesh Nagarajan, Ioannis Panageas, xiao wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1441-1449
Efficient Statistics for Sparse Graphical Models from Truncated Samples
Arnab Bhattacharyya, Rathin Desai, Sai Ganesh Nagarajan, Ioannis Panageas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1450-1458
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations.
Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1459-1467
Feedback Coding for Active Learning
Gregory Canal, Matthieu Bloch, Christopher Rozell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1468-1476
Shadow Manifold Hamiltonian Monte Carlo
Chris van der Heide, Fred Roosta, Liam Hodgkinson, Dirk Kroese; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1477-1485
Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms
Yilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1486-1494
Identification of Matrix Joint Block Diagonalization
Yunfeng Cai, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1495-1503
Understanding Gradient Clipping In Incremental Gradient Methods
Jiang Qian, Yuren Wu, Bojin Zhuang, Shaojun Wang, Jing Xiao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1504-1512
A Variational Information Bottleneck Approach to Multi-Omics Data Integration
Changhee Lee, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1513-1521
On the Privacy Properties of GAN-generated Samples
Zinan Lin, Vyas Sekar, Giulia Fanti; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1522-1530
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation
Zhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel Riek, Kamalika Chaudhuri; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1531-1539
Learning Complexity of Simulated Annealing
Avrim Blum, Chen Dan, Saeed Seddighin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1540-1548
Independent Innovation Analysis for Nonlinear Vector Autoregressive Process
Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvarinen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1549-1557
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers
Lunjia Hu, Omer Reingold; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1558-1566
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Ming Yin, Yu Bai, Yu-Xiang Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1567-1575
Q-learning with Logarithmic Regret
Kunhe Yang, Lin Yang, Simon Du; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1576-1584
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling
Qin Ding, Cho-Jui Hsieh, James Sharpnack; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1585-1593
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization
Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhiquan Luo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1594-1602
Robust and Private Learning of Halfspaces
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1603-1611
Minimax Model Learning
Cameron Voloshin, Nan Jiang, Yisong Yue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1612-1620
On the Faster Alternating Least-Squares for CCA
Zhiqiang Xu, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1621-1629
Exploiting Equality Constraints in Causal Inference
Chi Zhang, Carlos Cinelli, Bryant Chen, Judea Pearl; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1630-1638
Collaborative Classification from Noisy Labels
Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1639-1647
Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation
Han Bao, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1648-1656
Maximizing Agreements for Ranking, Clustering and Hierarchical Clustering via MAX-CUT
Vaggos Chatziafratis, Mohammad Mahdian, Sara Ahmadian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1657-1665
Why did the distribution change?
Kailash Budhathoki, Dominik Janzing, Patrick Bloebaum, Hoiyi Ng; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1666-1674
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Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers
Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1675-1683
Iterative regularization for convex regularizers
Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1684-1692
Competing AI: How does competition feedback affect machine learning?
Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1693-1701
Stability and Risk Bounds of Iterative Hard Thresholding
Xiaotong Yuan, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1702-1710
Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation
Yuki Ohnishi, Jean Honorio; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1711-1719
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow
Youssef Mroueh, Truyen Nguyen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1720-1728
Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects
Qiming Du, Gérard Biau, Francois Petit, Raphaël Porcher; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1729-1737
Improved Complexity Bounds in Wasserstein Barycenter Problem
Darina Dvinskikh, Daniil Tiapkin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1738-1746
Sparse Algorithms for Markovian Gaussian Processes
William Wilkinson, Arno Solin, Vincent Adam; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1747-1755
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
Lisa Schut, Oscar Key, Rory Mc Grath, Luca Costabello, Bogdan Sacaleanu, medb corcoran, Yarin Gal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1756-1764
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
Nina Vesseron, Ievgen Redko, Charlotte Laclau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1765-1773
All of the Fairness for Edge Prediction with Optimal Transport
Charlotte Laclau, Ievgen Redko, Manvi Choudhary, Christine Largeron; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1774-1782
γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator
Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1783-1791
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks
Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger Grosse, Joern-Henrik Jacobsen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1792-1800
Online probabilistic label trees
Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczynski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1801-1809
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1810-1818
DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation
Frederik Harder, Kamil Adamczewski, Mijung Park; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1819-1827
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, Wipf David; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1828-1836
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations
Simone Rossi, Markus Heinonen, Edwin Bonilla, Zheyang Shen, Maurizio Filippone; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1837-1845
Free-rider Attacks on Model Aggregation in Federated Learning
Yann Fraboni, Richard Vidal, Marco Lorenzi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1846-1854
Reinforcement Learning in Parametric MDPs with Exponential Families
Sayak Ray Chowdhury, Aditya Gopalan, Odalric-Ambrym Maillard; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1855-1863
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery
Mike Laszkiewicz, Asja Fischer, Johannes Lederer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1864-1872
No-regret Algorithms for Multi-task Bayesian Optimization
Sayak Ray Chowdhury, Aditya Gopalan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1873-1881
Explicit Regularization of Stochastic Gradient Methods through Duality
Anant Raj, Francis Bach; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1882-1890
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1891-1899
CONTRA: Contrarian statistics for controlled variable selection
Mukund Sudarshan, Aahlad Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1900-1908
Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning
Kai Cui, Heinz Koeppl; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1909-1917
Moment-Based Variational Inference for Stochastic Differential Equations
Christian Wildner, Heinz Koeppl; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1918-1926
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Alexander Lew, Monica Agrawal, David Sontag, Vikash Mansinghka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1927-1935
Adaptive wavelet pooling for convolutional neural networks
Moritz Wolter, Jochen Garcke; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1936-1944
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The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain
Fergus Simpson, Alexis Boukouvalas, Vaclav Cadek, Elvijs Sarkans, Nicolas Durrande; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1945-1953
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Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features
Shingo Yashima, Atsushi Nitanda, Taiji Suzuki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1954-1962
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding
Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1963-1971
Counterfactual Representation Learning with Balancing Weights
Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1972-1980
Gradient Descent in RKHS with Importance Labeling
Tomoya Murata, Taiji Suzuki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1981-1989
Learning with Gradient Descent and Weakly Convex Losses
Dominic Richards, Mike Rabbat; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1990-1998
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1999-2007
Approximate Data Deletion from Machine Learning Models
Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2008-2016
Budgeted and Non-Budgeted Causal Bandits
Vineet Nair, Vishakha Patil, Gaurav Sinha; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2017-2025
Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss
Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2026-2034
Equitable and Optimal Transport with Multiple Agents
Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2035-2043
A Variational Inference Approach to Learning Multivariate Wold Processes
Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2044-2052
Active Online Learning with Hidden Shifting Domains
Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2053-2061
No-Regret Algorithms for Private Gaussian Process Bandit Optimization
Abhimanyu Dubey; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2062-2070
The Teaching Dimension of Kernel Perceptron
Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2071-2079
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2080-2088
Localizing Changes in High-Dimensional Regression Models
Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett, Yi Yu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2089-2097
On the Suboptimality of Negative Momentum for Minimax Optimization
Guodong Zhang, Yuanhao Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2098-2106
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2107-2115
Corralling Stochastic Bandit Algorithms
Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2116-2124
Context-Specific Likelihood Weighting
Nitesh Kumar, Ondřej Kuželka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2125-2133
Learning Matching Representations for Individualized Organ Transplantation Allocation
Can Xu, Ahmed Alaa, Ioana Bica, Brent Ershoff, Maxime Cannesson, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2134-2142
Stochastic Gradient Descent Meets Distribution Regression
Nicole Muecke; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2143-2151
Learning Contact Dynamics using Physically Structured Neural Networks
Andreas Hochlehnert, Alexander Terenin, Steindor Saemundsson, Marc Deisenroth; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2152-2160
Misspecification in Prediction Problems and Robustness via Improper Learning
Annie Marsden, John Duchi, Gregory Valiant; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2161-2169
Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization
Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2170-2178
Selective Classification via One-Sided Prediction
Aditya Gangrade, Anil Kag, Venkatesh Saligrama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2179-2187
Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning
Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2188-2196
vqSGD: Vector Quantized Stochastic Gradient Descent
Venkata Gandikota, Daniel Kane, Raj Kumar Maity, Arya Mazumdar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2197-2205
Smooth Bandit Optimization: Generalization to Holder Space
Yusha Liu, Yining Wang, Aarti Singh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2206-2214
List Learning with Attribute Noise
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2215-2223
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation
Kristjan Greenewald, Karthikeyan Shanmugam, Dmitriy Katz; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2224-2232
Fractional moment-preserving initialization schemes for training deep neural networks
Mert Gurbuzbalaban, Yuanhan Hu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2233-2241
Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach
Yves-Laurent Kom Samo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2242-2250
Federated f-Differential Privacy
Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie Su; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2251-2259
Clustering multilayer graphs with missing nodes
Guillaume Braun, Hemant Tyagi, Christophe Biernacki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2260-2268
Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2269-2277
Aggregating Incomplete and Noisy Rankings
Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2278-2286
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models
Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2287-2295
Optimal query complexity for private sequential learning against eavesdropping
Jiaming Xu, Kuang Xu, Dana Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2296-2304
Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent
Suriya Gunasekar, Blake Woodworth, Nathan Srebro; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2305-2313
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Differentiable Causal Discovery Under Unmeasured Confounding
Rohit Bhattacharya, Tushar Nagarajan, Daniel Malinsky, Ilya Shpitser; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2314-2322
The Sample Complexity of Meta Sparse Regression
Zhanyu Wang, Jean Honorio; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2323-2331
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data
Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2332-2340
Group testing for connected communities
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas Diggavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2341-2349
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2350-2358
Variational Autoencoder with Learned Latent Structure
Marissa Connor, Gregory Canal, Christopher Rozell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2359-2367
RankDistil: Knowledge Distillation for Ranking
Sashank Reddi, Rama Kumar Pasumarthi, Aditya Menon, Ankit Singh Rawat, Felix Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2368-2376
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Thibaut Durand, Greg Mori; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2377-2385
On the Linear Convergence of Policy Gradient Methods for Finite MDPs
Jalaj Bhandari, Daniel Russo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2386-2394
Minimal enumeration of all possible total effects in a Markov equivalence class
Richard Guo, Emilija Perkovic; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2395-2403
Differentially Private Weighted Sampling
Edith Cohen, Ofir Geri, Tamas Sarlos, Uri Stemmer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2404-2412
Learning the Truth From Only One Side of the Story
Heinrich Jiang, Qijia Jiang, Aldo Pacchiano; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2413-2421
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
Yixing Zhang, Xiuyuan Cheng, Galen Reeves; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2422-2430
Bayesian Inference with Certifiable Adversarial Robustness
Matthew Wicker, Luca Laurenti, Andrea Patane, Zhuotong Chen, Zheng Zhang, Marta Kwiatkowska; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2431-2439
Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors
Benjamin Moseley, Sergei Vassilvtiskii, Yuyan Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2440-2448
Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference
Sean Plummer, Shuang Zhou, Anirban Bhattacharya, David Dunson, Debdeep Pati; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2449-2457
Reinforcement Learning for Mean Field Games with Strategic Complementarities
Kiyeob Lee, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2458-2466
Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
Sebastian Macaluso, Craig Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2467-2475
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
Chaoqi Wang, Shengyang Sun, Roger Grosse; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2476-2484
On the Consistency of Metric and Non-Metric K-Medoids
He Jiang, Ery Arias-Castro; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2485-2493
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Non-Stationary Off-Policy Optimization
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2494-2502
Efficient Interpolation of Density Estimators
Paxton Turner, Jingbo Liu, Philippe Rigollet; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2503-2511
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A Statistical Perspective on Coreset Density Estimation
Paxton Turner, Jingbo Liu, Philippe Rigollet; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2512-2520
Shuffled Model of Differential Privacy in Federated Learning
Antonious Girgis, Deepesh Data, Suhas Diggavi, Peter Kairouz, Ananda Theertha Suresh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2521-2529
CLAR: Contrastive Learning of Auditory Representations
Haider Al-Tahan, Yalda Mohsenzadeh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2530-2538
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Designing Transportable Experiments Under S-admissability
My Phan, David Arbour, Drew Dimmery, Anup Rao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2539-2547
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
Gauthier Gidel, David Balduzzi, Wojciech Czarnecki, Marta Garnelo, Yoram Bachrach; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2548-2556
Private optimization without constraint violations
Andres Munoz, Umar Syed, Sergei Vassilvtiskii, Ellen Vitercik; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2557-2565
Direct Loss Minimization for Sparse Gaussian Processes
Yadi Wei, Rishit Sheth, Roni Khardon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2566-2574
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary Charles, Jakub Konečný; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2575-2583
Linear Models are Robust Optimal Under Strategic Behavior
Wei Tang, Chien-Ju Ho, Yang Liu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2584-2592
Matérn Gaussian Processes on Graphs
Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Deisenroth, Nicolas Durrande; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2593-2601
Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
Alden Green, Sivaraman Balakrishnan, Ryan Tibshirani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2602-2610
Evaluating Model Robustness and Stability to Dataset Shift
Adarsh Subbaswamy, Roy Adams, Suchi Saria; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2611-2619
Continuum-Armed Bandits: A Function Space Perspective
Shashank Singh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2620-2628
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Regret-Optimal Filtering
Oron Sabag, Babak Hassibi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2629-2637
Evading the Curse of Dimensionality in Unconstrained Private GLMs
Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2638-2646
One-Sketch-for-All: Non-linear Random Features from Compressed Linear Measurements
Xiaoyun Li, Ping Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2647-2655
Reinforcement Learning for Constrained Markov Decision Processes
Ather Gattami, Qinbo Bai, Vaneet Aggarwal; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2656-2664
Principal Component Regression with Semirandom Observations via Matrix Completion
Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2665-2673
Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2674-2682
Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
Shengjia Zhao, Stefano Ermon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2683-2691
Sample Elicitation
Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2692-2700
Random Coordinate Underdamped Langevin Monte Carlo
Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen Wright; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2701-2709
Influence Decompositions For Neural Network Attribution
Kyle Reing, Greg Ver Steeg, Aram Galstyan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2710-2718
Variational inference for nonlinear ordinary differential equations
Sanmitra Ghosh, Paul Birrell, Daniela De Angelis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2719-2727
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization
Moses Charikar, Lunjia Hu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2728-2736
Fast Adaptation with Linearized Neural Networks
Wesley Maddox, Shuai Tang, Pablo Moreno, Andrew Gordon Wilson, Andreas Damianou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2737-2745
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2746-2754
A Change of Variables Method For Rectangular Matrix-Vector Products
Edmond Cunningham, Madalina Fiterau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2755-2763
Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case
Yufeng Zhang, Zhuoran Yang, Zhaoran Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2764-2772
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions
Hossein Taheri, Ramtin Pedarsani, Christos Thrampoulidis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2773-2781
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2782-2790
Causal Inference with Selectively Deconfounded Data
Kyra Gan, Andrew Li, Zachary Lipton, Sridhar Tayur; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2791-2799
Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model
Libby Zhang, Tim Dunn, Jesse Marshall, Bence Olveczky, Scott Linderman; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2800-2808
Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan, Kartik Gupta, Philip Torr, Richad Hartley, Puneet Dokania; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2809-2817
Power of Hints for Online Learning with Movement Costs
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2818-2826
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Stochastic Bandits with Linear Constraints
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, Heinrich Jiang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2827-2835
Significance of Gradient Information in Bayesian Optimization
Shubhanshu Shekhar, Tara Javidi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2836-2844
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2845-2853
DAG-Structured Clustering by Nearest Neighbors
Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2854-2862
Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning
Yunhao Tang, Alp Kucukelbir; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2863-2871
Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2872-2880
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Location Trace Privacy Under Conditional Priors
Casey Meehan, Kamalika Chaudhuri; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2881-2889
Large Scale K-Median Clustering for Stable Clustering Instances
Konstantin Voevodski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2890-2898
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An Optimal Reduction of TV-Denoising to Adaptive Online Learning
Dheeraj Baby, Xuandong Zhao, Yu-Xiang Wang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2899-2907
Differentially Private Monotone Submodular Maximization Under Matroid and Knapsack Constraints
Omid Sadeghi, Maryam Fazel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2908-2916
Federated Multi-armed Bandits with Personalization
Chengshuai Shi, Cong Shen, Jing Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2917-2925
Hierarchical Inducing Point Gaussian Process for Inter-domian Observations
Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David Blei, John Cunningham; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2926-2934
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression
Yifan Chen, Yun Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2935-2943
Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms
Tianyu Ding, Zhihui Zhu, Manolis Tsakiris, Rene Vidal, Daniel Robinson; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2944-2952
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Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression
Yifan Chen, Yun Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2953-2961
Robust hypothesis testing and distribution estimation in Hellinger distance
Ananda Theertha Suresh; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2962-2970
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Faster Kernel Interpolation for Gaussian Processes
Mohit Yadav, Daniel Sheldon, Cameron Musco; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2971-2979
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups
Hyun-Suk Lee, Cong Shen, William Zame, Jang-Won Lee, Mihaela van der Schaar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2980-2988
Detection and Defense of Topological Adversarial Attacks on Graphs
Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2989-2997
Training a Single Bandit Arm
Eren Ozbay, Vijay Kamble; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2998-3006
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
Chen-Yu Wei, Mehdi Jafarnia Jahromi, Haipeng Luo, Rahul Jain; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3007-3015
Multi-Armed Bandits with Cost Subsidy
Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni, Vashist Avadhanula; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3016-3024
Causal Modeling with Stochastic Confounders
Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze Yun Leong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3025-3033
The Multiple Instance Learning Gaussian Process Probit Model
Fulton Wang, Ali Pinar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3034-3042
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
Hunter Lang, Aravind Reddy, David Sontag, Aravindan Vijayaraghavan; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3043-3051
Meta Learning in the Continuous Time Limit
Ruitu Xu, Lin Chen, Amin Karbasi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3052-3060
Fast and Smooth Interpolation on Wasserstein Space
Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin Stromme; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3061-3069
Efficient Balanced Treatment Assignments for Experimentation
David Arbour, Drew Dimmery, Anup Rao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3070-3078
Tensor Networks for Probabilistic Sequence Modeling
Jacob Miller, Guillaume Rabusseau, John Terilla; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3079-3087
Experimental Design for Regret Minimization in Linear Bandits
Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3088-3096
DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks
Shiyun Xu, Zhiqi Bu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3097-3105
Dynamic Cutset Networks
Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3106-3114
Associative Convolutional Layers
Hamed Omidvar, Vahideh Akhlaghi, Hao Su, Massimo Franceschetti, Rajesh Gupta; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3115-3123
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
Jeremiah Liu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3124-3132
Kernel Interpolation for Scalable Online Gaussian Processes
Samuel Stanton, Wesley Maddox, Ian Delbridge, Andrew Gordon Wilson; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3133-3141
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
Huichen Li, Linyi Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3142-3150
Contrastive learning of strong-mixing continuous-time stochastic processes
Bingbin Liu, Pradeep Ravikumar, Andrej Risteski; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3151-3159
TenIPS: Inverse Propensity Sampling for Tensor Completion
Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3160-3168
Sketch based Memory for Neural Networks
Rina Panigrahy, Xin Wang, Manzil Zaheer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3169-3177
Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression
Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan Tibshirani; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3178-3186
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
Zhiqi Bu, Shiyun Xu, Kan Chen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3187-3195
Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees
Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, Stephen Bach; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3196-3204
Principal Subspace Estimation Under Information Diffusion
Fan Zhou, Ping Li, Zhixin Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3205-3213
A Hybrid Approximation to the Marginal Likelihood
Eric Chuu, Debdeep Pati, Anirban Bhattacharya; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3214-3222
Prediction with Finitely many Errors Almost Surely
Changlong Wu, Narayana Santhanam; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3223-3231
Density of States Estimation for Out of Distribution Detection
Warren Morningstar, Cusuh Ham, Andrew Gallagher, Balaji Lakshminarayanan, Alex Alemi, Joshua Dillon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3232-3240
Product Manifold Learning
Sharon Zhang, Amit Moscovich, Amit Singer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3241-3249
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Automatic Differentiation Variational Inference with Mixtures
Warren Morningstar, Sharad Vikram, Cusuh Ham, Andrew Gallagher, Joshua Dillon; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3250-3258
Fair for All: Best-effort Fairness Guarantees for Classification
Anilesh Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng, Kamesh Munagala; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3259-3267
Taming heavy-tailed features by shrinkage
Ziwei Zhu, Wenjing Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3268-3276
Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension
Yiliang Zhang, Zhiqi Bu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3277-3285
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
Mayee Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Re; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3286-3294
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Frederik Kunstner, Raunak Kumar, Mark Schmidt; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3295-3303
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3304-3312
Understanding Robustness in Teacher-Student Setting: A New Perspective
Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3313-3321
Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences
Sreejith Sreekumar, Zhengxin Zhang, Ziv Goldfeld; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3322-3330
Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning
Zhengqing Zhou, Zhengyuan Zhou, Qinxun Bai, Linhai Qiu, Jose Blanchet, Peter Glynn; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3331-3339
Online Model Selection for Reinforcement Learning with Function Approximation
Jonathan Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3340-3348
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC
Priyank Jaini, Didrik Nielsen, Max Welling; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3349-3357
Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT
Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3358-3366
A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits
Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3367-3375
Good Classifiers are Abundant in the Interpolating Regime
Ryan Theisen, Jason Klusowski, Michael Mahoney; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3376-3384
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No-Regret Reinforcement Learning with Heavy-Tailed Rewards
Vincent Zhuang, Yanan Sui; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3385-3393
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A Spectral Analysis of Dot-product Kernels
Meyer Scetbon, Zaid Harchaoui; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3394-3402
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Towards Flexible Device Participation in Federated Learning
Yichen Ruan, Xiaoxi Zhang, Shu-Che Liang, Carlee Joe-Wong; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3403-3411
Active Learning under Label Shift
Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3412-3420
Tracking Regret Bounds for Online Submodular Optimization
Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3421-3429
Offline detection of change-points in the mean for stationary graph signals.
Alejandro de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3430-3438
Hyperbolic graph embedding with enhanced semi-implicit variational inference.
Ali Lotfi Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan Tamir; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3439-3447
Rao-Blackwellised parallel MCMC
Tobias Schwedes, Ben Calderhead; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3448-3456
Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression
Ian Covert, Su-In Lee; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3457-3465
Calibrated Adaptive Probabilistic ODE Solvers
Nathanael Bosch, Philipp Hennig, Filip Tronarp; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3466-3474
Online Robust Control of Nonlinear Systems with Large Uncertainty
Dimitar Ho, Hoang Le, John Doyle, Yisong Yue; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3475-3483
Probabilistic Sequential Matrix Factorization
Omer Deniz Akyildiz, Gerrit van den Burg, Theodoros Damoulas, Mark Steel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3484-3492
An Analysis of LIME for Text Data
Dina Mardaoui, Damien Garreau; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3493-3501
Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information
Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3502-3510
Scalable Gaussian Process Variational Autoencoders
Metod Jazbec, Matt Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3511-3519
Causal Autoregressive Flows
Ilyes Khemakhem, Ricardo Monti, Robert Leech, Aapo Hyvarinen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3520-3528
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
Jan Achterhold, Joerg Stueckler; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3529-3537
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3538-3546
Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov, Maxim Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3547-3555
Local SGD: Unified Theory and New Efficient Methods
Eduard Gorbunov, Filip Hanzely, Peter Richtarik; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3556-3564
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
Alexander Camuto, Matthew Willetts, Stephen Roberts, Chris Holmes, Tom Rainforth; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3565-3573
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Vikas Garg, Adam Tauman Kalai, Katrina Ligett, Steven Wu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3574-3582
The Base Measure Problem and its Solution
Alexey Radul, Boris Alexeev; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3583-3591
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Revisiting Projection-free Online Learning: the Strongly Convex Case
Ben Kretzu, Dan Garber; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3592-3600
A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models
Samet Oymak, Talha Cihad Gulcu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3601-3609
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Logistic Q-Learning
Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3610-3618
Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
Nafiseh Ghoroghchian, Gautam Dasarathy, Stark Draper; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3619-3627
Sequential Random Sampling Revisited: Hidden Shuffle Method
Michael Shekelyan, Graham Cormode; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3628-3636
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Dirichlet Pruning for Convolutional Neural Networks
Kamil Adamczewski, Mijung Park; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3637-3645
Couplings for Multinomial Hamiltonian Monte Carlo
Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3646-3654
Learning Bijective Feature Maps for Linear ICA
Alexander Camuto, Matthew Willetts, Chris Holmes, Brooks Paige, Stephen Roberts; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3655-3663
Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain
Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3664-3672
One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks
Hanjing Zhu, Jiaming Xu; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3673-3681
On the Memory Mechanism of Tensor-Power Recurrent Models
Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3682-3690
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille, Louis Faury, Clement Calauzenes; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3691-3699
Causal Inference under Networked Interference and Intervention Policy Enhancement
Yunpu Ma, Volker Tresp; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3700-3708
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
Mucong Ding, Constantinos Daskalakis, Soheil Feizi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3709-3717
Latent Gaussian process with composite likelihoods and numerical quadrature
Siddharth Ramchandran, Miika Koskinen, Harri Lähdesmäki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3718-3726
Deep Generative Missingness Pattern-Set Mixture Models
Sahra Ghalebikesabi, Rob Cornish, Chris Holmes, Luke Kelly; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3727-3735
Minimax Estimation of Laplacian Constrained Precision Matrices
Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel Palomar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3736-3744
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models
Jiaxin Zhang, Sirui Bi, Guannan Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3745-3753
Distribution Regression for Sequential Data
Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin Bonilla, Terry Lyons; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3754-3762
Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions
Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, Stephan Günnemann; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3763-3771
Direct-Search for a Class of Stochastic Min-Max Problems
Sotirios-Konstantinos Anagnostidis, Aurelien Lucchi, Youssef Diouane; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3772-3780
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry
Qadeer Khan, Patrick Wenzel, Daniel Cremers; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3781-3789
Learning Temporal Point Processes with Intermittent Observations
Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3790-3798
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On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity
Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3799-3807
Robust Learning under Strong Noise via SQs
Ioannis Anagnostides, Themis Gouleakis, Ali Marashian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3808-3816
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
Leena C. Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3817-3825
Convergence Properties of Stochastic Hypergradients
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3826-3834
Entropy Partial Transport with Tree Metrics: Theory and Practice
Tam Le, Truyen Nguyen; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3835-3843
Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms
Ilker Demirel, Cem Tekin; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3844-3852
Differentiable Divergences Between Time Series
Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3853-3861
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning
Konstantinos Panousis, Sotirios Chatzis, Antonios Alexos, Sergios Theodoridis; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3862-3870
Differentiating the Value Function by using Convex Duality
Sheheryar Mehmood, Peter Ochs; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3871-3879
Rate-Regularization and Generalization in Variational Autoencoders
Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana Brooks, Jennifer Dy, Jan-Willem van de Meent; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3880-3888
Asymptotics of Ridge(less) Regression under General Source Condition
Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3889-3897
Longitudinal Variational Autoencoder
Siddharth Ramchandran, Gleb Tikhonov, Kalle Kujanpää, Miika Koskinen, Harri Lähdesmäki; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3898-3906
An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo
Matthew Hoffman, Alexey Radul, Pavel Sountsov; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3907-3915
Model updating after interventions paradoxically introduces bias
James Liley, Samuel Emerson, Bilal Mateen, Catalina Vallejos, Louis Aslett, Sebastian Vollmer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3916-3924
On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models
Yuyang Shi, Rob Cornish; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3925-3933
Flow-based Alignment Approaches for Probability Measures in Different Spaces
Tam Le, Nhat Ho, Makoto Yamada; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3934-3942
LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads
Hossein Shokri Ghadikolaei, Sebastian Stich, Martin Jaggi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3943-3951
Learning Shared Subgraphs in Ising Model Pairs
Burak Varici, Saurabh Sihag, Ali Tajer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3952-3960
Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling
Setareh Ariafar, Zelda Mariet, Dana Brooks, Jennifer Dy, Jasper Snoek; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3961-3969
Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty
Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3970-3978
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization
Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand, Thomas Hofmann, Roy S. Smith; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3979-3987
Improved Exploration in Factored Average-Reward MDPs
Mohammad Sadegh Talebi, Anders Jonsson, Odalric Maillard; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3988-3996
Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries
Steve Hanneke, Liu Yang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:3997-4005
Regularized ERM on random subspaces
Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4006-4014
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4015-4023
Meta-Learning Divergences for Variational Inference
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4024-4032
Hidden Cost of Randomized Smoothing
Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4033-4041
Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates
Sebastian Stich, Amirkeivan Mohtashami, Martin Jaggi; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4042-4050
Improving Classifier Confidence using Lossy Label-Invariant Transformations
Sooyong Jang, Insup Lee, James Weimer; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4051-4059
Graph Gamma Process Linear Dynamical Systems
Rahi Kalantari, Mingyuan Zhou; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4060-4068
Does Invariant Risk Minimization Capture Invariance?
Pritish Kamath, Akilesh Tangella, Danica Sutherland, Nathan Srebro; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4069-4077
A unified view of likelihood ratio and reparameterization gradients
Paavo Parmas, Masashi Sugiyama; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4078-4086
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtarik, Sebastian Stich; Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:4087-4095
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