General Keywords

[ Algorithms ] [ Algorithms; Optimization ] [ Applications ] [ Data, Challenges, Implementations, and Software ] [ Deep Learning ] [ Deep Learning; Deep Learning ] [ Neuroscience and Cognitive Science ] [ Optimization ] [ Optimization; Optimization ] [ Probabilistic Methods ] [ Probabilistic Methods; Probabilistic Methods ] [ Reinforcement Learning and Planning ] [ Social Aspects of Machine Learning ] [ Theory ] [ Theory; Theory ]

Topic Keywords

[ Active Learning ] [ Active Learning; Algorithms ] [ Activity and Event Recognition ] [ Adaptive Data Analysis; Optimization ] [ Adversarial Examples ] [ Adversarial Learning ] [ Adversarial Learning; Algorithms ] [ Adversarial Networks ] [ Adversarial Networks ] [ Adversarial Networks; Deep Learning ] [ Adversarial Networks; Deep Learning ] [ AI Safety ] [ Algorithms Evaluation ] [ Approximate Inference ] [ Architectures ] [ Attention Models ] [ Audio and Speech Processing ] [ AutoML ] [ Bandit Algorithms ] [ Bandit Algorithms; Algorithms ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandits ] [ Bayesian Deep Learning ] [ Bayesian Methods ] [ Bayesian Nonparametrics ] [ Bayesian Theory ] [ Bayesian Theory ] [ Benchmarks ] [ Biologically Plausible Deep Networks ] [ Biologically Plausible Deep Networks; Deep Learning ] [ Biologically Plausible Deep Networks; Neuroscience and Cognitive Science ] [ Body Pose, Face, and Gesture Analysis ] [ Body Pose, Face, and Gesture Analysis; Applications ] [ Boosting and Ensemble Methods ] [ Boosting and Ensemble Methods; Algorithms ] [ Boosting and Ensemble Methods; Probabilistic Methods; Probabilistic Methods ] [ Causal Inference ] [ Classification ] [ Classification; Algorithms ] [ Classification; Algorithms ] [ Classification; Applications ] [ Classification; Deep Learning; Deep Learning ] [ Classification; Deep Learning; Deep Learning ] [ Clustering ] [ Clustering; Applications ] [ Clustering; Theory ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Theory ] [ Cognitive Science; Neuroscience and Cognitive Science ] [ Collaborative Filtering ] [ Collaborative Filtering; Algorithms ] [ Collaborative Filtering; Applications ] [ Combinatorial Optimization ] [ Components Analysis (e.g., CCA, ICA, LDA, PCA) ] [ Computational Biology and Bioinformatics ] [ Computational Biology and Bioinformatics; Applications ] [ Computational Complexity ] [ Computational Learning Theory ] [ Computational Photography ] [ Computational Social Science ] [ Computer Vision ] [ Computer Vision; Applications ] [ Computer Vision; Applications ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Continual Learning ] [ Convex Optimization ] [ Convex Optimization; Optimization ] [ Convex Optimization; Probabilistic Methods; Theory; Theory ] [ Convex Optimization; Theory ] [ Crowdsourcing ] [ Decision and Control ] [ Deep Autoencoders; Deep Learning ] [ Deep learning Theory ] [ Deep RL ] [ Density Estimation ] [ Density Estimation; Deep Learning ] [ Derivative Free Optimization ] [ Dialog- or Communication-Based Learning ] [ Dimensionality Reduction ] [ Distributed and Parallel Optimization ] [ Distributed Inference ] [ Efficient Inference Methods ] [ Efficient Training Methods; Deep Learning ] [ Embedding and Representation learning ] [ Embedding Approaches ] [ Exploration ] [ Fairness, Accountability, and Transparency ] [ Fairness, Accountability, and Transparency ] [ Few-Shot Learning ] [ Few-Shot Learning; Algorithms ] [ Frequentist Statistics ] [ Game Theory and Computational Economics ] [ Gaussian Processes ] [ Gaussian Processes and Bayesian non-parametrics ] [ Generative Models ] [ Generative Models ] [ Graphical Models ] [ Graphical Models ] [ Hardware and Systems ] [ Healthcare ] [ Human or Animal Learning ] [ Human or Animal Learning; Probabilistic Methods ] [ Image Segmentation ] [ Image Segmentation; Algorithms ] [ Image Segmentation; Applications ] [ Information Theory ] [ Kernel Methods ] [ Kernel Methods; Optimization ] [ Large Deviations and Asymptotic Analysis ] [ Large Scale Learning ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Applications ] [ Large Scale Learning; Deep Learning ] [ Large Scale Learning; Probabilistic Methods ] [ Latent Variable Models ] [ Learning Theory ] [ Markov Decision Processes ] [ Markov Decision Processes; Reinforcement Learning and Planning ] [ Markov Decision Processes; Reinforcement Learning and Planning ] [ Matrix and Tensor Factorization ] [ MCMC ] [ Memory ] [ Memory; Optimization ] [ Meta-Learning ] [ Meta-Learning; Applications ] [ Metric Learning ] [ Missing Data; Algorithms ] [ Missing Data; Algorithms ] [ Missing Data; Theory ] [ Model Selection and Structure Learning ] [ Models of Learning and Generalization ] [ Monte Carlo Methods ] [ Multi-Agent RL ] [ Multimodal Learning ] [ Multitask and Transfer Learning ] [ Multitask and Transfer Learning; Algorithms ] [ Multitask and Transfer Learning; Probabilistic Methods ] [ Multitask, Transfer, and Meta Learning ] [ Natural Language Processing ] [ Network Analysis ] [ Networks and Relational Learning ] [ Neural Coding; Neuroscience and Cognitive Science ] [ Neuroscience ] [ Neuroscience and Cognitive Science ] [ Non-Convex Optimization ] [ Non-Convex Optimization ] [ Non-Convex Optimization; Theory ] [ Non-parametric models ] [ Object Detection; Deep Learning ] [ Object Detection; Neuroscience and Cognitive Science ] [ Online Learning ] [ Online Learning Algorithms ] [ Online Learning Theory ] [ Online Learning; Theory ] [ Optimal Transport ] [ Optimization for Deep Networks ] [ Others ] [ Others ] [ Others ] [ Others ] [ Others ] [ Planning and Control ] [ Plasticity and Adaptation ] [ Predictive Models ] [ Predictive Models; Deep Learning ] [ Predictive Models; Deep Learning ] [ Privacy, Anonymity, and Security ] [ Privacy, Anonymity, and Security ] [ Probabilistic Methods ] [ Probabilistic Programming ] [ Program Understanding and Generation ] [ Quantitative Finance and Econometrics ] [ Ranking and Preference Learning ] [ Ranking and Preference Learning; Theory ] [ Reasoning; Optimization ] [ Recommender Systems ] [ Recurrent Networks ] [ Recurrent Networks; Theory ] [ Regression ] [ Regression; Algorithms ] [ Regression; Applications ] [ Regression; Optimization ] [ Regression; Probabilistic Methods; Probabilistic Methods ] [ Regularization ] [ Regularization ] [ Reinforcement Learning ] [ Reinforcement Learning and Planning ] [ Relational Learning ] [ Representation Learning ] [ Representation Learning; Algorithms ] [ Representation Learning; Algorithms ] [ Representation Learning; Neuroscience and Cognitive Science ] [ Representation Learning; Neuroscience and Cognitive Science; Neuroscience and Cognitive Science ] [ Representation Learning; Optimization ] [ RL, Decisions and Control Theory ] [ Robotics ] [ Robust statistics ] [ Semi-Supervised Learning ] [ Social Aspects of Machine Learning ] [ Software Toolkits ] [ Spaces of Functions and Kernels ] [ Sparse Coding and Dimensionality Expansion; Applications ] [ Sparsity and Compressed Sensing ] [ Sparsity and Compressed Sensing; Applications ] [ Sparsity and Compressed Sensing; Optimization; Theory ] [ Speech Recognition ] [ Statistical Learning Theory ] [ Statistical Physics of Learning ] [ Stochastic Optimization ] [ Structured Prediction ] [ Submodular Optimization ] [ Supervised Learning ] [ Sustainability and Environment ] [ Theory ] [ Time Series Analysis ] [ Time Series Analysis; Deep Learning ] [ Time Series Analysis; Probabilistic Methods; Probabilistic Methods ] [ Time Series and Sequences ] [ Topic Models ] [ Uncertainty Estimation ] [ Uncertainty Estimation; Applications; Probabilistic Methods ] [ Unsupervised Learning ] [ Unsupervised Learning; Applications ] [ Unsupervised Learning; Deep Learning ] [ Variational Inference ] [ Visualization or Exposition Techniques for Deep Networks ] [ Visual Question Answering ] [ Visual Scene Analysis and Interpretation ]

644 Results

Affinity Workshop
Mon 9:15 OCDE: Odds Conditional Density Estimator
Alex Aki Okuno, Felipe Polo
Tutorial
Mon 12:00 Online and non-stochastic control
Elad Hazan, Karan Singh
Tutorial
Mon 12:00 Random Matrix Theory and ML (RMT+ML)
Fabian Pedregosa, Courtney Paquette, Thomas Trogdon, Jeffrey Pennington
Affinity Workshop
Mon 15:15 A Tree-Adaptation Mechanism for Covariate and Concept Drift
Leno Silva, Renato Vicente
Oral
Tue 5:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Oral
Tue 5:00 Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Spotlight
Tue 5:20 Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik
Spotlight
Tue 5:20 Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Spotlight
Tue 5:30 Breaking the Limits of Message Passing Graph Neural Networks
Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine
Spotlight
Tue 5:35 Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Oral Session
Tue 6:00 Deep Learning Theory 1
Spotlight
Tue 6:20 Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai
Spotlight
Tue 6:25 A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Spotlight
Tue 6:25 Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Spotlight
Tue 6:30 Distributionally Robust Optimization with Markovian Data
Mengmeng Li, Tobias Sutter, Daniel Kuhn
Spotlight
Tue 6:30 PID Accelerated Value Iteration Algorithm
Amir-massoud Farahmand, Mohammad Ghavamzadeh
Spotlight
Tue 6:30 Continual Learning in the Teacher-Student Setup: Impact of Task Similarity
Sebastian Lee, Sebastian Goldt, Andrew Saxe
Spotlight
Tue 6:35 A Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna
Spotlight
Tue 7:20 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Anima Anandkumar
Spotlight
Tue 7:20 Learning Bounds for Open-Set Learning
Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang
Spotlight
Tue 7:30 Grid-Functioned Neural Networks
Javier Dehesa, Andrew Vidler, Julian Padget, Christof Lutteroth
Spotlight
Tue 7:40 Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theo Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos
Spotlight
Tue 7:45 DeepWalking Backwards: From Embeddings Back to Graphs
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Babis Tsourakakis
Spotlight
Tue 7:45 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 Distributionally Robust Optimization with Markovian Data
Mengmeng Li, Tobias Sutter, Daniel Kuhn
Poster
Tue 9:00 Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Poster
Tue 9:00 Breaking the Limits of Message Passing Graph Neural Networks
Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine
Poster
Tue 9:00 Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai
Poster
Tue 9:00 A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Poster
Tue 9:00 Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Poster
Tue 9:00 Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik
Poster
Tue 9:00 Learning Bounds for Open-Set Learning
Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang
Poster
Tue 9:00 A Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna
Poster
Tue 9:00 Continual Learning in the Teacher-Student Setup: Impact of Task Similarity
Sebastian Lee, Sebastian Goldt, Andrew Saxe
Poster
Tue 9:00 PID Accelerated Value Iteration Algorithm
Amir-massoud Farahmand, Mohammad Ghavamzadeh
Poster
Tue 9:00 Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Poster
Tue 9:00 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Poster
Tue 9:00 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Anima Anandkumar
Poster
Tue 9:00 Grid-Functioned Neural Networks
Javier Dehesa, Andrew Vidler, Julian Padget, Christof Lutteroth
Poster
Tue 9:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Poster
Tue 9:00 Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theo Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos
Poster
Tue 9:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Poster
Tue 9:00 DeepWalking Backwards: From Embeddings Back to Graphs
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Babis Tsourakakis
Spotlight
Tue 17:20 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Spotlight
Tue 17:25 Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Spotlight
Tue 17:30 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Spotlight
Tue 17:30 On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith Ross
Spotlight
Tue 17:30 Joining datasets via data augmentation in the label space for neural networks
Jake Zhao Zhao, Mingfeng Ou, linji Xue, Yunkai Cui, Sai Wu, Gang Chen
Spotlight
Tue 17:45 LARNet: Lie Algebra Residual Network for Face Recognition
Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu
Oral
Tue 18:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Spotlight
Tue 18:20 Regularized Submodular Maximization at Scale
Ehsan Kazemi, shervin minaee, Moran Feldman, Amin Karbasi
Spotlight
Tue 18:20 The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
Spotlight
Tue 18:30 On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan Chatapuram Krishnan
Spotlight
Tue 18:30 On Estimation in Latent Variable Models
Guanhua Fang, Ping Li
Spotlight
Tue 18:30 LAMDA: Label Matching Deep Domain Adaptation
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
Spotlight
Tue 18:35 Light RUMs
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins
Oral
Tue 19:00 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph E Gonzalez
Oral
Tue 19:00 Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen
Spotlight
Tue 19:20 Revisiting Peng's Q($\lambda$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, Dave Abel
Spotlight
Tue 19:20 Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu
Spotlight
Tue 19:25 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Spotlight
Tue 19:30 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Spotlight
Tue 19:35 Neural Rough Differential Equations for Long Time Series
James Morrill, Cristopher Salvi, Patrick Kidger, James Foster
Spotlight
Tue 19:40 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wes Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Spotlight
Tue 19:45 Reinforcement Learning Under Moral Uncertainty
Adrien Ecoffet, Joel Lehman
Poster
Tue 21:00 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Poster
Tue 21:00 LAMDA: Label Matching Deep Domain Adaptation
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
Poster
Tue 21:00 Light RUMs
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins
Poster
Tue 21:00 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Poster
Tue 21:00 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph E Gonzalez
Poster
Tue 21:00 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Poster
Tue 21:00 The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
Poster
Tue 21:00 LARNet: Lie Algebra Residual Network for Face Recognition
Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu
Poster
Tue 21:00 Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Poster
Tue 21:00 On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan Chatapuram Krishnan
Poster
Tue 21:00 Regularized Submodular Maximization at Scale
Ehsan Kazemi, shervin minaee, Moran Feldman, Amin Karbasi
Poster
Tue 21:00 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wes Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Poster
Tue 21:00 On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith Ross
Poster
Tue 21:00 On Estimation in Latent Variable Models
Guanhua Fang, Ping Li
Poster
Tue 21:00 Joining datasets via data augmentation in the label space for neural networks
Jake Zhao Zhao, Mingfeng Ou, linji Xue, Yunkai Cui, Sai Wu, Gang Chen
Poster
Tue 21:00 Neural Rough Differential Equations for Long Time Series
James Morrill, Cristopher Salvi, Patrick Kidger, James Foster
Poster
Tue 21:00 Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen
Poster
Tue 21:00 Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu
Poster
Tue 21:00 Revisiting Peng's Q($\lambda$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, Dave Abel
Poster
Tue 21:00 Reinforcement Learning Under Moral Uncertainty
Adrien Ecoffet, Joel Lehman
Poster
Tue 21:00 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Oral
Wed 5:00 Near Optimal Reward-Free Reinforcement Learning
Zhang Zihan, Simon Du, Xiangyang Ji
Oral Session
Wed 5:00 Learning Theory 2
Oral Session
Wed 5:00 Learning Theory 3
Oral
Wed 5:00 On Energy-Based Models with Overparametrized Shallow Neural Networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
Oral Session
Wed 5:00 Deep Learning Theory 2
Oral
Wed 5:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Oral Session
Wed 5:00 Learning Theory 1
Oral
Wed 5:00 Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Spotlight
Wed 5:20 Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
Gen Li, Yuantao Gu
Spotlight
Wed 5:20 Generalization Bounds in the Presence of Outliers: a Median-of-Means Study
Pierre Laforgue, Guillaume Staerman, Stephan Clémençon
Spotlight
Wed 5:20 Uncertainty Principles of Encoding GANs
TaiGe Feng, Zhouchen Lin, jiapeng zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha
Spotlight
Wed 5:20 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Spotlight
Wed 5:25 Approximating a Distribution Using Weight Queries
Nadav Barak, Sivan Sabato
Spotlight
Wed 5:25 Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen
Spotlight
Wed 5:25 Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
Qian Zhang, Yilin Zheng, Jean Honorio
Spotlight
Wed 5:25 On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh Nguyen
Spotlight
Wed 5:30 Robust Inference for High-Dimensional Linear Models via Residual Randomization
Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar
Spotlight
Wed 5:30 Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
Spotlight
Wed 5:35 Bootstrapping Fitted Q-Evaluation for Off-Policy Inference
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang
Spotlight
Wed 5:35 Functional Space Analysis of Local GAN Convergence
Valentin Khrulkov, Artem Babenko, Ivan Oseledets
Spotlight
Wed 5:35 Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
Yu Bai, Song Mei, Huan Wang, Caiming Xiong
Spotlight
Wed 5:35 Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
Ryan Henderson, Djork-Arné Clevert, Floriane Montanari
Spotlight
Wed 5:35 Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing
Yuan Deng, Sébastien Lahaie, Vahab Mirrokni, Song Zuo
Spotlight
Wed 5:40 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki
Spotlight
Wed 5:40 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei
Spotlight
Wed 5:40 Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi
Spotlight
Wed 5:40 Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Hima Lakkaraju
Spotlight
Wed 5:45 Spectral vertex sparsifiers and pair-wise spanners over distributed graphs
Chunjiang Zhu, Qinqing Liu, Jinbo Bi
Spotlight
Wed 5:45 Optimal Estimation of High Dimensional Smooth Additive Function Based on Noisy Observations
Fan Zhou, Ping Li
Spotlight
Wed 5:45 Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu
Spotlight
Wed 5:45 Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, FLORENT KRZAKALA, Lenka Zdeborova
Oral
Wed 6:00 Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Oral
Wed 6:00 Bilinear Classes: A Structural Framework for Provable Generalization in RL
Simon Du, Sham Kakade, Jason Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
Oral
Wed 6:00 Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, CHEN Chen, Evangelos Theodorou
Oral
Wed 6:00 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu
Oral Session
Wed 6:00 Game Theory and Econ
Oral Session
Wed 6:00 Learning Theory 4
Oral Session
Wed 6:00 Reinforcement Learning Theory 1
Spotlight
Wed 6:20 Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering
Romain COUILLET, Florent Chatelain, Nicolas Le Bihan
Spotlight
Wed 6:20 Align, then memorise: the dynamics of learning with feedback alignment
Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt
Spotlight
Wed 6:20 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li
Spotlight
Wed 6:20 Selecting Data Augmentation for Simulating Interventions
Max Ilse, Jakub Tomczak, Patrick Forré
Spotlight
Wed 6:20 How could Neural Networks understand Programs?
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
Spotlight
Wed 6:25 Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results
Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm
Spotlight
Wed 6:25 Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with √T Regret
Asaf Cassel, Tomer Koren
Spotlight
Wed 6:25 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Spotlight
Wed 6:30 Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Spotlight
Wed 6:30 Estimation and Quantization of Expected Persistence Diagrams
Vincent Divol, Theo Lacombe
Spotlight
Wed 6:30 Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kiran Shiragur, Stefano Ermon
Spotlight
Wed 6:30 Learning to Price Against a Moving Target
Renato Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah
Spotlight
Wed 6:35 Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
Yun Kuen Cheung, Georgios Piliouras
Spotlight
Wed 6:35 Post-selection inference with HSIC-Lasso
Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada
Spotlight
Wed 6:40 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Spotlight
Wed 6:40 On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP
Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang
Spotlight
Wed 6:40 Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou, Spencer Frei, Quanquan Gu
Spotlight
Wed 6:45 An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
Spotlight
Wed 6:45 Kernel-Based Reinforcement Learning: A Finite-Time Analysis
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Spotlight
Wed 6:45 Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees
Kishan Panaganti, Dileep Kalathil
Spotlight
Wed 6:45 Incentivizing Compliance with Algorithmic Instruments
Daniel Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu
Spotlight
Wed 6:45 Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting
Chirag Gupta, Aaditya Ramdas
Oral
Wed 7:00 Modelling Behavioural Diversity for Learning in Open-Ended Games
Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers, David Mguni, Ying Wen, Jun Wang
Oral Session
Wed 7:00 Deep Learning Theory 3
Oral Session
Wed 7:00 Learning Theory 5
Oral
Wed 7:00 Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev
Oral Session
Wed 7:00 Learning Theory 6
Oral
Wed 7:00 On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake Woodworth, Nati Srebro, Amir Globerson, Daniel Soudry
Oral
Wed 7:00 PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao
Spotlight
Wed 7:15 Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi
Spotlight
Wed 7:20 Variance Reduced Training with Stratified Sampling for Forecasting Models
Yucheng Lu, Youngsuk Park, Lifan Chen, Bernie Wang, Christopher De Sa, Dean Foster
Spotlight
Wed 7:20 Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan NOIRY
Spotlight
Wed 7:20 Follow-the-Regularized-Leader Routes to Chaos in Routing Games
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski, Michał Misiurewicz, Georgios Piliouras
Spotlight
Wed 7:20 A statistical perspective on distillation
Aditya Menon, Ankit Singh Rawat, Sashank Jakkam Reddi, Seungyeon Kim, Sanjiv Kumar
Spotlight
Wed 7:25 Generalised Lipschitz Regularisation Equals Distributional Robustness
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith
Spotlight
Wed 7:25 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Spotlight
Wed 7:25 Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, M. Li, Ying Wen, Joel Jennings, Jun Wang
Spotlight
Wed 7:25 The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih
Spotlight
Wed 7:25 Necessary and sufficient conditions for causal feature selection in time series with latent common causes
Atalanti Mastakouri, Bernhard Schölkopf, Dominik Janzing
Spotlight
Wed 7:25 A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel Robinson, Enrique Mallada, Rene Vidal
Spotlight
Wed 7:30 Revealing the Structure of Deep Neural Networks via Convex Duality
Tolga Ergen, Mert Pilanci
Spotlight
Wed 7:30 Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
Spotlight
Wed 7:30 Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris
Spotlight
Wed 7:35 Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Spotlight
Wed 7:35 Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James Wright, Michael Bowling, Amy Greenwald
Spotlight
Wed 7:35 Large-Scale Multi-Agent Deep FBSDEs
Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos Theodorou
Spotlight
Wed 7:35 Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam, Benjamin Van Roy
Spotlight
Wed 7:40 Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang
Spotlight
Wed 7:40 Collaborative Bayesian Optimization with Fair Regret
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet
Spotlight
Wed 7:40 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Spotlight
Wed 7:40 Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
Spotlight
Wed 7:45 AGENT: A Benchmark for Core Psychological Reasoning
Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Josh Tenenbaum, Tomer Ullman
Spotlight
Wed 7:45 The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning
Roberto Bondesan, Max Welling
Spotlight
Wed 7:45 One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao
Poster
Wed 9:00 Necessary and sufficient conditions for causal feature selection in time series with latent common causes
Atalanti Mastakouri, Bernhard Schölkopf, Dominik Janzing
Poster
Wed 9:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Poster
Wed 9:00 Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev
Poster
Wed 9:00 Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, M. Li, Ying Wen, Joel Jennings, Jun Wang
Poster
Wed 9:00 Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with √T Regret
Asaf Cassel, Tomer Koren
Poster
Wed 9:00 Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu
Poster
Wed 9:00 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu
Poster
Wed 9:00 On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake Woodworth, Nati Srebro, Amir Globerson, Daniel Soudry
Poster
Wed 9:00 Incentivizing Compliance with Algorithmic Instruments
Daniel Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu
Poster
Wed 9:00 Relative Deviation Margin Bounds
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
Poster
Wed 9:00 Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting
Chirag Gupta, Aaditya Ramdas
Poster
Wed 9:00 Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kiran Shiragur, Stefano Ermon
Poster
Wed 9:00 AGENT: A Benchmark for Core Psychological Reasoning
Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Josh Tenenbaum, Tomer Ullman
Poster
Wed 9:00 Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, CHEN Chen, Evangelos Theodorou
Poster
Wed 9:00 Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering
Romain COUILLET, Florent Chatelain, Nicolas Le Bihan
Poster
Wed 9:00 Align, then memorise: the dynamics of learning with feedback alignment
Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt
Poster
Wed 9:00 Functional Space Analysis of Local GAN Convergence
Valentin Khrulkov, Artem Babenko, Ivan Oseledets
Poster
Wed 9:00 On Energy-Based Models with Overparametrized Shallow Neural Networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
Poster
Wed 9:00 Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
Ryan Henderson, Djork-Arné Clevert, Floriane Montanari
Poster
Wed 9:00 The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih
Poster
Wed 9:00 Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees
Kishan Panaganti, Dileep Kalathil
Poster
Wed 9:00 Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
Yu Bai, Song Mei, Huan Wang, Caiming Xiong
Poster
Wed 9:00 The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning
Roberto Bondesan, Max Welling
Poster
Wed 9:00 Generalization Bounds in the Presence of Outliers: a Median-of-Means Study
Pierre Laforgue, Guillaume Staerman, Stephan Clémençon
Poster
Wed 9:00 On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh Nguyen
Poster
Wed 9:00 Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
Poster
Wed 9:00 Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Poster
Wed 9:00 Selecting Data Augmentation for Simulating Interventions
Max Ilse, Jakub Tomczak, Patrick Forré
Poster
Wed 9:00 Variance Reduced Training with Stratified Sampling for Forecasting Models
Yucheng Lu, Youngsuk Park, Lifan Chen, Bernie Wang, Christopher De Sa, Dean Foster
Poster
Wed 9:00 Approximating a Distribution Using Weight Queries
Nadav Barak, Sivan Sabato
Poster
Wed 9:00 Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi
Poster
Wed 9:00 Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang
Poster
Wed 9:00 Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou, Spencer Frei, Quanquan Gu
Poster
Wed 9:00 Spectral vertex sparsifiers and pair-wise spanners over distributed graphs
Chunjiang Zhu, Qinqing Liu, Jinbo Bi
Poster
Wed 9:00 Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
Poster
Wed 9:00 Large-Scale Multi-Agent Deep FBSDEs
Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos Theodorou
Poster
Wed 9:00 Uncertainty Principles of Encoding GANs
TaiGe Feng, Zhouchen Lin, jiapeng zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha
Poster
Wed 9:00 A statistical perspective on distillation
Aditya Menon, Ankit Singh Rawat, Sashank Jakkam Reddi, Seungyeon Kim, Sanjiv Kumar
Poster
Wed 9:00 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Poster
Wed 9:00 How could Neural Networks understand Programs?
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
Poster
Wed 9:00 A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel Robinson, Enrique Mallada, Rene Vidal
Poster
Wed 9:00 Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris
Poster
Wed 9:00 Bootstrapping Fitted Q-Evaluation for Off-Policy Inference
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang
Poster
Wed 9:00 Bilinear Classes: A Structural Framework for Provable Generalization in RL
Simon Du, Sham Kakade, Jason Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
Poster
Wed 9:00 Learning to Price Against a Moving Target
Renato Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah
Poster
Wed 9:00 PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao
Poster
Wed 9:00 Robust Inference for High-Dimensional Linear Models via Residual Randomization
Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar
Poster
Wed 9:00 Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, FLORENT KRZAKALA, Lenka Zdeborova
Poster
Wed 9:00 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki
Poster
Wed 9:00 Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
Qian Zhang, Yilin Zheng, Jean Honorio
Poster
Wed 9:00 Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Poster
Wed 9:00 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Poster
Wed 9:00 Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen
Poster
Wed 9:00 One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao
Poster
Wed 9:00 Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Poster
Wed 9:00 Kernel-Based Reinforcement Learning: A Finite-Time Analysis
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Poster
Wed 9:00 Collaborative Bayesian Optimization with Fair Regret
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet
Poster
Wed 9:00 An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
Poster
Wed 9:00 Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Poster
Wed 9:00 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li
Poster
Wed 9:00 Optimal Estimation of High Dimensional Smooth Additive Function Based on Noisy Observations
Fan Zhou, Ping Li
Poster
Wed 9:00 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Poster
Wed 9:00 Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James Wright, Michael Bowling, Amy Greenwald
Poster
Wed 9:00 Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
Poster
Wed 9:00 Generalised Lipschitz Regularisation Equals Distributional Robustness
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith
Poster
Wed 9:00 Follow-the-Regularized-Leader Routes to Chaos in Routing Games
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski, Michał Misiurewicz, Georgios Piliouras
Poster
Wed 9:00 Estimation and Quantization of Expected Persistence Diagrams
Vincent Divol, Theo Lacombe
Poster
Wed 9:00 Modelling Behavioural Diversity for Learning in Open-Ended Games
Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers, David Mguni, Ying Wen, Jun Wang
Poster
Wed 9:00 Near Optimal Reward-Free Reinforcement Learning
Zhang Zihan, Simon Du, Xiangyang Ji
Poster
Wed 9:00 Post-selection inference with HSIC-Lasso
Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada
Poster
Wed 9:00 On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP
Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang
Poster
Wed 9:00 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Poster
Wed 9:00 Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
Yun Kuen Cheung, Georgios Piliouras
Poster
Wed 9:00 Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam, Benjamin Van Roy
Poster
Wed 9:00 Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
Gen Li, Yuantao Gu
Poster
Wed 9:00 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Poster
Wed 9:00 Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Hima Lakkaraju
Poster
Wed 9:00 Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi
Poster
Wed 9:00 Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing
Yuan Deng, Sébastien Lahaie, Vahab Mirrokni, Song Zuo
Poster
Wed 9:00 Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results
Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm
Poster
Wed 9:00 Revealing the Structure of Deep Neural Networks via Convex Duality
Tolga Ergen, Mert Pilanci
Poster
Wed 9:00 Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan NOIRY
Poster
Wed 9:00 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei
Oral
Wed 17:00 Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Oral
Wed 17:00 UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre MENARD, Omar Darwiche Domingues, Xuedong Shang, Michal Valko
Oral Session
Wed 17:00 Deep Learning Theory 4
Oral
Wed 17:00 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
Oral Session
Wed 17:00 Reinforcement Learning Theory 3
Oral
Wed 17:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Oral
Wed 17:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Oral
Wed 17:00 Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah
Oral Session
Wed 17:00 Reinforcement Learning Theory 2
Oral Session
Wed 17:00 Learning Theory 7
Oral
Wed 17:00 Learning Optimal Auctions with Correlated Valuations from Samples
CHUNXUE YANG, Xiaohui Bei
Oral Session
Wed 17:00 Learning Theory 8
Spotlight
Wed 17:20 Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Alexander D Camuto, Xiaoyu Wang, Lingjiong Zhu, Christopher Holmes, Mert Gurbuzbalaban, Umut Simsekli
Spotlight
Wed 17:20 Alternative Microfoundations for Strategic Classification
Meena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt
Spotlight
Wed 17:20 Near-Optimal Linear Regression under Distribution Shift
Qi Lei, Wei Hu, Jason Lee
Spotlight
Wed 17:25 Detection of Signal in the Spiked Rectangular Models
Ji Hyung Jung, Hye Won Chung, Ji Oon Lee
Spotlight
Wed 17:25 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Spotlight
Wed 17:25 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
Spotlight
Wed 17:25 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Spotlight
Wed 17:25 Multi-Receiver Online Bayesian Persuasion
Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti
Spotlight
Wed 17:30 A Distribution-dependent Analysis of Meta Learning
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvari
Spotlight
Wed 17:30 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Spotlight
Wed 17:30 Online Learning for Load Balancing of Unknown Monotone Resource Allocation Games
Ilai Bistritz, Nicholas Bambos
Spotlight
Wed 17:30 Near-Optimal Representation Learning for Linear Bandits and Linear RL
Jiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang
Spotlight
Wed 17:30 FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
Spotlight
Wed 17:30 Fast active learning for pure exploration in reinforcement learning
Pierre MENARD, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko
Spotlight
Wed 17:35 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Spotlight
Wed 17:35 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Spotlight
Wed 17:35 A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions
Gabriel Mel, Surya Ganguli
Spotlight
Wed 17:35 Compressed Maximum Likelihood
Yi Hao, Alon Orlitsky
Spotlight
Wed 17:35 Improved OOD Generalization via Adversarial Training and Pretraing
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma
Spotlight
Wed 17:35 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Spotlight
Wed 17:35 How Important is the Train-Validation Split in Meta-Learning?
Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong
Spotlight
Wed 17:40 Robust Unsupervised Learning via L-statistic Minimization
Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil
Spotlight
Wed 17:40 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon, Ernest Ryu
Spotlight
Wed 17:40 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Spotlight
Wed 17:40 Robust Policy Gradient against Strong Data Corruption
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
Spotlight
Wed 17:40 Consistent regression when oblivious outliers overwhelm
Tommaso d'Orsi, Gleb Novikov, David Steurer
Spotlight
Wed 17:45 A Theory of Label Propagation for Subpopulation Shift
Tianle Cai, Ruiqi Gao, Jason Lee, Qi Lei
Spotlight
Wed 17:45 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Spotlight
Wed 17:45 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Spotlight
Wed 17:45 Asymptotics of Ridge Regression in Convolutional Models
Moji Sahraee-Ardakan, Tung Mai, Anup Rao, Ryan A. Rossi, Sundeep Rangan, Alyson Fletcher
Oral Session
Wed 18:00 Deep Learning Theory 5
Oral
Wed 18:00 Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
Oral Session
Wed 18:00 Reinforcement Learning Theory 4
Oral
Wed 18:00 Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Oral
Wed 18:00 Dissecting Supervised Constrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt
Oral
Wed 18:00 Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Oral Session
Wed 18:00 Learning Theory 10
Oral
Wed 18:00 Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
Oral
Wed 18:00 RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton
Oral Session
Wed 18:00 Learning Theory 11
Oral Session
Wed 18:00 Learning Theory 9
Spotlight
Wed 18:20 Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
Spotlight
Wed 18:20 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
Spotlight
Wed 18:20 Online Learning in Unknown Markov Games
Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra
Spotlight
Wed 18:20 Outside the Echo Chamber: Optimizing the Performative Risk
John Miller, Juan Perdomo, Tijana Zrnic
Spotlight
Wed 18:20 KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
Spotlight
Wed 18:25 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Spotlight
Wed 18:25 On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models
Peizhong Ju, Xiaojun Lin, Ness Shroff
Spotlight
Wed 18:25 Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator
Zeng Li, Chuanlong Xie, Qinwen Wang
Spotlight
Wed 18:25 An Information-Geometric Distance on the Space of Tasks
Yansong Gao, Pratik Chaudhari
Spotlight
Wed 18:25 Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward Hu
Spotlight
Wed 18:25 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Spotlight
Wed 18:30 Randomized Exploration in Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang
Spotlight
Wed 18:30 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin LIANG
Spotlight
Wed 18:30 Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier, Renyuan Xu
Spotlight
Wed 18:30 On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, rendong Ying, Chao Ma, Peilin Liu
Spotlight
Wed 18:30 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea
Spotlight
Wed 18:30 Provable Meta-Learning of Linear Representations
Nilesh Tripuraneni, Chi Jin, Michael Jordan
Spotlight
Wed 18:35 Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
Changhun Jo, Kangwook Lee
Spotlight
Wed 18:35 On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada
Spotlight
Wed 18:35 Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Spotlight
Wed 18:35 Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
Yujia Jin, Aaron Sidford
Spotlight
Wed 18:35 Sample Complexity of Robust Linear Classification on Separated Data
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Spotlight
Wed 18:35 Event Outlier Detection in Continuous Time
Siqi Liu, Milos Hauskrecht
Spotlight
Wed 18:40 Relative Deviation Margin Bounds
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
Spotlight
Wed 18:40 Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
Spotlight
Wed 18:40 Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case
Liyu Chen, Haipeng Luo
Spotlight
Wed 18:40 Model Performance Scaling with Multiple Data Sources
Tatsunori Hashimoto
Spotlight
Wed 18:40 The Impact of Record Linkage on Learning from Feature Partitioned Data
Richard Nock, Stephen J Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne
Spotlight
Wed 18:45 Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Spotlight
Wed 18:45 Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
Spotlight
Wed 18:45 Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Spotlight
Wed 18:45 Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Tae Hyun Cho, Jungwoo Lee
Oral
Wed 19:00 Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, Shashanka Ubaru
Oral Session
Wed 19:00 Learning Theory 12
Oral Session
Wed 19:00 Learning Theory 13
Oral Session
Wed 19:00 Reinforcement Learning Theory 5
Oral
Wed 19:00 A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
Oral
Wed 19:00 Improved Regret Bound and Experience Replay in Regularized Policy Iteration
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari
Oral
Wed 19:00 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville
Spotlight
Wed 19:20 Sample-Optimal PAC Learning of Halfspaces with Malicious Noise
Jie Shen
Spotlight
Wed 19:20 Lower-Bounded Proper Losses for Weakly Supervised Classification
Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama
Spotlight
Wed 19:20 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Spotlight
Wed 19:25 On Robust Mean Estimation under Coordinate-level Corruption
Zifan Liu, Jongho Park, Theo Rekatsinas, Christos Tzamos
Spotlight
Wed 19:25 On Variational Inference in Biclustering Models
Guanhua Fang, Ping Li
Spotlight
Wed 19:30 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
Spotlight
Wed 19:30 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Spotlight
Wed 19:30 Multidimensional Scaling: Approximation and Complexity
Erik Demaine, Adam C Hesterberg, Frederic Koehler, Jayson Lynch, John C Urschel
Spotlight
Wed 19:35 Toward Better Generalization Bounds with Locally Elastic Stability
Zhun Deng, Hangfeng He, Weijie Su
Spotlight
Wed 19:35 Dropout: Explicit Forms and Capacity Control
Raman Arora, Peter Bartlett, Poorya Mianjy, Nati Srebro
Spotlight
Wed 19:35 Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Spotlight
Wed 19:40 Finding Relevant Information via a Discrete Fourier Expansion
Mohsen Heidari, Jithin Sreedharan, Gil Shamir, Wojciech Szpankowski
Spotlight
Wed 19:40 12-Lead ECG Reconstruction via Koopman Operators
Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha
Spotlight
Wed 19:40 Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
Spotlight
Wed 19:45 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
Spotlight
Wed 19:45 On the Inherent Regularization Effects of Noise Injection During Training
Oussama Dhifallah, Yue Lu
Spotlight
Wed 19:45 Interpreting and Disentangling Feature Components of Various Complexity from DNNs
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Poster
Wed 21:00 Sample Complexity of Robust Linear Classification on Separated Data
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Poster
Wed 21:00 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
Poster
Wed 21:00 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Poster
Wed 21:00 Learning Optimal Auctions with Correlated Valuations from Samples
CHUNXUE YANG, Xiaohui Bei
Poster
Wed 21:00 Near-Optimal Representation Learning for Linear Bandits and Linear RL
Jiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang
Poster
Wed 21:00 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Poster
Wed 21:00 Fast active learning for pure exploration in reinforcement learning
Pierre MENARD, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko
Poster
Wed 21:00 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Poster
Wed 21:00 UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre MENARD, Omar Darwiche Domingues, Xuedong Shang, Michal Valko
Poster
Wed 21:00 KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
Poster
Wed 21:00 Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator
Zeng Li, Chuanlong Xie, Qinwen Wang
Poster
Wed 21:00 Lower-Bounded Proper Losses for Weakly Supervised Classification
Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama
Poster
Wed 21:00 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Poster
Wed 21:00 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin LIANG
Poster
Wed 21:00 On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models
Peizhong Ju, Xiaojun Lin, Ness Shroff
Poster
Wed 21:00 Compressed Maximum Likelihood
Yi Hao, Alon Orlitsky
Poster
Wed 21:00 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Poster
Wed 21:00 Near-Optimal Linear Regression under Distribution Shift
Qi Lei, Wei Hu, Jason Lee
Poster
Wed 21:00 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Poster
Wed 21:00 Event Outlier Detection in Continuous Time
Siqi Liu, Milos Hauskrecht
Poster
Wed 21:00 Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
Poster
Wed 21:00 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Poster
Wed 21:00 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Poster
Wed 21:00 Online Learning for Load Balancing of Unknown Monotone Resource Allocation Games
Ilai Bistritz, Nicholas Bambos
Poster
Wed 21:00 Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Alexander D Camuto, Xiaoyu Wang, Lingjiong Zhu, Christopher Holmes, Mert Gurbuzbalaban, Umut Simsekli
Poster
Wed 21:00 Outside the Echo Chamber: Optimizing the Performative Risk
John Miller, Juan Perdomo, Tijana Zrnic
Poster
Wed 21:00 Alternative Microfoundations for Strategic Classification
Meena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt
Poster
Wed 21:00 Sample-Optimal PAC Learning of Halfspaces with Malicious Noise
Jie Shen
Poster
Wed 21:00 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Poster
Wed 21:00 Multi-Receiver Online Bayesian Persuasion
Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti
Poster
Wed 21:00 Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, Shashanka Ubaru
Poster
Wed 21:00 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Poster
Wed 21:00 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Poster
Wed 21:00 The Impact of Record Linkage on Learning from Feature Partitioned Data
Richard Nock, Stephen J Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne
Poster
Wed 21:00 Improved Regret Bound and Experience Replay in Regularized Policy Iteration
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari
Poster
Wed 21:00 Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah
Poster
Wed 21:00 Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
Poster
Wed 21:00 Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Tae Hyun Cho, Jungwoo Lee
Poster
Wed 21:00 Robust Unsupervised Learning via L-statistic Minimization
Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil
Poster
Wed 21:00 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Poster
Wed 21:00 Provable Meta-Learning of Linear Representations
Nilesh Tripuraneni, Chi Jin, Michael Jordan
Poster
Wed 21:00 Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Poster
Wed 21:00 Online Learning in Unknown Markov Games
Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra
Poster
Wed 21:00 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
Poster
Wed 21:00 Model Performance Scaling with Multiple Data Sources
Tatsunori Hashimoto
Poster
Wed 21:00 On the Inherent Regularization Effects of Noise Injection During Training
Oussama Dhifallah, Yue Lu
Poster
Wed 21:00 A Theory of Label Propagation for Subpopulation Shift
Tianle Cai, Ruiqi Gao, Jason Lee, Qi Lei
Poster
Wed 21:00 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Poster
Wed 21:00 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville
Poster
Wed 21:00 Toward Better Generalization Bounds with Locally Elastic Stability
Zhun Deng, Hangfeng He, Weijie Su
Poster
Wed 21:00 Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
Poster
Wed 21:00 Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Poster
Wed 21:00 Dissecting Supervised Constrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt
Poster
Wed 21:00 Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
Yujia Jin, Aaron Sidford
Poster
Wed 21:00 Randomized Exploration in Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang
Poster
Wed 21:00 How Important is the Train-Validation Split in Meta-Learning?
Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong
Poster
Wed 21:00 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
Poster
Wed 21:00 A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
Poster
Wed 21:00 Asymptotics of Ridge Regression in Convolutional Models
Moji Sahraee-Ardakan, Tung Mai, Anup Rao, Ryan A. Rossi, Sundeep Rangan, Alyson Fletcher
Poster
Wed 21:00 Multidimensional Scaling: Approximation and Complexity
Erik Demaine, Adam C Hesterberg, Frederic Koehler, Jayson Lynch, John C Urschel
Poster
Wed 21:00 Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Poster
Wed 21:00 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
Poster
Wed 21:00 A Distribution-dependent Analysis of Meta Learning
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvari
Poster
Wed 21:00 Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
Changhun Jo, Kangwook Lee
Poster
Wed 21:00 On Variational Inference in Biclustering Models
Guanhua Fang, Ping Li
Poster
Wed 21:00 Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Poster
Wed 21:00 Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Poster
Wed 21:00 Finding Relevant Information via a Discrete Fourier Expansion
Mohsen Heidari, Jithin Sreedharan, Gil Shamir, Wojciech Szpankowski
Poster
Wed 21:00 12-Lead ECG Reconstruction via Koopman Operators
Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha
Poster
Wed 21:00 Robust Policy Gradient against Strong Data Corruption
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
Poster
Wed 21:00 Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Poster
Wed 21:00 RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton
Poster
Wed 21:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Poster
Wed 21:00 Interpreting and Disentangling Feature Components of Various Complexity from DNNs
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Poster
Wed 21:00 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon, Ernest Ryu
Poster
Wed 21:00 On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, rendong Ying, Chao Ma, Peilin Liu
Poster
Wed 21:00 Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier, Renyuan Xu
Poster
Wed 21:00 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea
Poster
Wed 21:00 On Robust Mean Estimation under Coordinate-level Corruption
Zifan Liu, Jongho Park, Theo Rekatsinas, Christos Tzamos
Poster
Wed 21:00 Dropout: Explicit Forms and Capacity Control
Raman Arora, Peter Bartlett, Poorya Mianjy, Nati Srebro
Poster
Wed 21:00 On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada
Poster
Wed 21:00 Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Poster
Wed 21:00 A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions
Gabriel Mel, Surya Ganguli
Poster
Wed 21:00 An Information-Geometric Distance on the Space of Tasks
Yansong Gao, Pratik Chaudhari
Poster
Wed 21:00 Detection of Signal in the Spiked Rectangular Models
Ji Hyung Jung, Hye Won Chung, Ji Oon Lee
Poster
Wed 21:00 Improved OOD Generalization via Adversarial Training and Pretraing
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma
Poster
Wed 21:00 Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
Poster
Wed 21:00 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Poster
Wed 21:00 Consistent regression when oblivious outliers overwhelm
Tommaso d'Orsi, Gleb Novikov, David Steurer
Poster
Wed 21:00 FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
Poster
Wed 21:00 Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case
Liyu Chen, Haipeng Luo
Poster
Wed 21:00 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
Poster
Wed 21:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Poster
Wed 21:00 Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
Poster
Wed 21:00 Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward Hu
Poster
Wed 21:00 Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
Oral
Thu 5:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Oral
Thu 5:00 Local Algorithms for Finding Densely Connected Clusters
Peter Macgregor, He Sun
Oral
Thu 5:00 Tilting the playing field: Dynamical loss functions for machine learning
Miguel Ruiz Garcia, Ge Zhang, Samuel Schoenholz, Andrea Liu
Oral Session
Thu 5:00 Deep Learning Theory 6
Spotlight
Thu 5:20 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Spotlight
Thu 5:25 Implicit Bias of Linear RNNs
Melika Emami, Moji Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher
Spotlight
Thu 5:30 Analyzing the tree-layer structure of Deep Forests
Ludovic Arnould, Claire Boyer, Erwan Scornet
Spotlight
Thu 5:35 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
Eran Malach, Pritish Kamath, Emmanuel Abbe, Nati Srebro
Spotlight
Thu 5:40 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Spotlight
Thu 5:40 Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen
Spotlight
Thu 5:45 Directional Bias Amplification
Angelina Wang, Olga Russakovsky
Spotlight
Thu 5:45 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Spotlight
Thu 5:45 Uniform Convergence, Adversarial Spheres and a Simple Remedy
Gregor Bachmann, Seyed Moosavi, Thomas Hofmann
Oral
Thu 6:00 Temporal Difference Learning as Gradient Splitting
Rui Liu, Alex Olshevsky
Oral
Thu 6:00 Differentially Private Query Release Through Adaptive Projection
Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit Siva
Oral
Thu 6:00 Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander Levine, Soheil Feizi
Oral Session
Thu 6:00 Learning Theory 14
Spotlight
Thu 6:20 Differentially Private Quantiles
Jennifer Gillenwater, Matthew Joseph, Alex Kulesza
Spotlight
Thu 6:20 First-Order Methods for Wasserstein Distributionally Robust MDP
Julien Grand-Clement, Christian Kroer
Spotlight
Thu 6:25 Finite mixture models do not reliably learn the number of components
Diana Cai, Trevor Campbell, Tamara Broderick
Spotlight
Thu 6:25 Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc
Spotlight
Thu 6:30 Adaptive Sampling for Best Policy Identification in Markov Decision Processes
Aymen Al Marjani, Alexandre Proutiere
Spotlight
Thu 6:30 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Spotlight
Thu 6:30 Disambiguation of Weak Supervision leading to Exponential Convergence rates
Vivien Cabannnes, Francis Bach, Alessandro Rudi
Spotlight
Thu 6:35 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
Spotlight
Thu 6:35 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Spotlight
Thu 6:35 Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi
Spotlight
Thu 6:45 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong
Oral
Thu 7:00 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Guha Thakurta, Li Zhang
Spotlight
Thu 7:20 Enhancing Robustness of Neural Networks through Fourier Stabilization
Netanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik
Spotlight
Thu 7:35 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Poster
Thu 9:00 Differentially Private Query Release Through Adaptive Projection
Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit Siva
Poster
Thu 9:00 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Poster
Thu 9:00 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Guha Thakurta, Li Zhang
Poster
Thu 9:00 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Poster
Thu 9:00 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong
Poster
Thu 9:00 Enhancing Robustness of Neural Networks through Fourier Stabilization
Netanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik
Poster
Thu 9:00 Implicit Bias of Linear RNNs
Melika Emami, Moji Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher
Poster
Thu 9:00 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Poster
Thu 9:00 Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc
Poster
Thu 9:00 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Poster
Thu 9:00 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
Eran Malach, Pritish Kamath, Emmanuel Abbe, Nati Srebro
Poster
Thu 9:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Poster
Thu 9:00 Temporal Difference Learning as Gradient Splitting
Rui Liu, Alex Olshevsky
Poster
Thu 9:00 Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen
Poster
Thu 9:00 Uniform Convergence, Adversarial Spheres and a Simple Remedy
Gregor Bachmann, Seyed Moosavi, Thomas Hofmann
Poster
Thu 9:00 Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi
Poster
Thu 9:00 First-Order Methods for Wasserstein Distributionally Robust MDP
Julien Grand-Clement, Christian Kroer
Poster
Thu 9:00 Directional Bias Amplification
Angelina Wang, Olga Russakovsky
Poster
Thu 9:00 Local Algorithms for Finding Densely Connected Clusters
Peter Macgregor, He Sun
Poster
Thu 9:00 Analyzing the tree-layer structure of Deep Forests
Ludovic Arnould, Claire Boyer, Erwan Scornet
Poster
Thu 9:00 Adaptive Sampling for Best Policy Identification in Markov Decision Processes
Aymen Al Marjani, Alexandre Proutiere
Poster
Thu 9:00 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
Poster
Thu 9:00 Disambiguation of Weak Supervision leading to Exponential Convergence rates
Vivien Cabannnes, Francis Bach, Alessandro Rudi
Poster
Thu 9:00 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Poster
Thu 9:00 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Poster
Thu 9:00 Differentially Private Quantiles
Jennifer Gillenwater, Matthew Joseph, Alex Kulesza
Poster
Thu 9:00 Tilting the playing field: Dynamical loss functions for machine learning
Miguel Ruiz Garcia, Ge Zhang, Samuel Schoenholz, Andrea Liu
Poster
Thu 9:00 Finite mixture models do not reliably learn the number of components
Diana Cai, Trevor Campbell, Tamara Broderick
Poster
Thu 9:00 Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander Levine, Soheil Feizi
Oral
Thu 17:00 Probabilistic Generating Circuits
Honghua Zhang, Brendan Juba, Guy Van den Broeck
Spotlight
Thu 17:20 Unitary Branching Programs: Learnability and Lower Bounds
Fidel Ernesto Diaz Andino, Maria Kokkou, Mateus de Oliveira Oliveira, Farhad Vadiee
Spotlight
Thu 17:25 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Spotlight
Thu 17:25 Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Chiang, Vyas Sekar
Spotlight
Thu 17:30 Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning
Yonghan Jung, Jin Tian, Elias Bareinboim
Oral
Thu 18:00 Label Inference Attacks from Log-loss Scores
Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Seyi Feyisetan, Nathanael Teissier
Spotlight
Thu 18:25 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Spotlight
Thu 18:25 Watermarking Deep Neural Networks with Greedy Residuals
Hanwen Liu, Zhenyu Weng, Yuesheng Zhu
Spotlight
Thu 18:25 CountSketches, Feature Hashing and the Median of Three
Kasper Green Larsen, Rasmus Pagh, Jakub Tětek
Spotlight
Thu 18:30 Meta-Thompson Sampling
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari
Spotlight
Thu 18:30 Efficient Online Learning for Dynamic k-Clustering
Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis
Spotlight
Thu 18:30 Average-Reward Off-Policy Policy Evaluation with Function Approximation
Shangtong Zhang, Yi Wan, Richard Sutton, Shimon Whiteson
Spotlight
Thu 18:35 Active Slices for Sliced Stein Discrepancy
Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jose Miguel Hernandez-Lobato
Spotlight
Thu 18:40 Few-shot Language Coordination by Modeling Theory of Mind
Hao Zhu, Graham Neubig, Yonatan Bisk
Spotlight
Thu 18:45 Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
Spotlight
Thu 19:00 Explaining Time Series Predictions with Dynamic Masks
Jonathan Crabbé, Mihaela van der Schaar
Oral
Thu 19:00 A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Spotlight
Thu 19:20 FILTRA: Rethinking Steerable CNN by Filter Transform
Bo Li, Qili Wang, Gim Hee Lee
Spotlight
Thu 19:20 Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph Lim, Byoung-Tak Zhang
Spotlight
Thu 19:35 GBHT: Gradient Boosting Histogram Transform for Density Estimation
Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin
Spotlight
Thu 19:40 Testing Group Fairness via Optimal Transport Projections
Nian Si, Karthyek Murthy, Jose Blanchet, Viet Anh Nguyen
Spotlight
Thu 19:40 Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh
Spotlight
Thu 19:45 Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
Tianyu Ding, Zhihui Zhu, Rene Vidal, Daniel Robinson
Spotlight
Thu 20:30 Discretization Drift in Two-Player Games
Mihaela Rosca, Yan Wu, Benoit Dherin, David GT Barrett
Spotlight
Thu 20:35 Elementary superexpressive activations
Dmitry Yarotsky
Spotlight
Thu 20:35 Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
Spotlight
Thu 20:40 Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
Spotlight
Thu 20:45 Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert, Ziv Goldfeld, Kengo Kato
Spotlight
Thu 20:45 Learner-Private Convex Optimization
Jiaming Xu, Kuang Xu, Dana Yang
Spotlight
Thu 20:50 How rotational invariance of common kernels prevents generalization in high dimensions
Konstantin Donhauser, Mingqi Wu, Fanny Yang
Poster
Thu 21:00 Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert, Ziv Goldfeld, Kengo Kato
Poster
Thu 21:00 Unitary Branching Programs: Learnability and Lower Bounds
Fidel Ernesto Diaz Andino, Maria Kokkou, Mateus de Oliveira Oliveira, Farhad Vadiee
Poster
Thu 21:00 Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph Lim, Byoung-Tak Zhang
Poster
Thu 21:00 Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Chiang, Vyas Sekar
Poster
Thu 21:00 Learner-Private Convex Optimization
Jiaming Xu, Kuang Xu, Dana Yang
Poster
Thu 21:00 FILTRA: Rethinking Steerable CNN by Filter Transform
Bo Li, Qili Wang, Gim Hee Lee
Poster
Thu 21:00 Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
Poster
Thu 21:00 Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning
Yonghan Jung, Jin Tian, Elias Bareinboim
Poster
Thu 21:00 Watermarking Deep Neural Networks with Greedy Residuals
Hanwen Liu, Zhenyu Weng, Yuesheng Zhu
Poster
Thu 21:00 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Poster
Thu 21:00 Explaining Time Series Predictions with Dynamic Masks
Jonathan Crabbé, Mihaela van der Schaar
Poster
Thu 21:00 How rotational invariance of common kernels prevents generalization in high dimensions
Konstantin Donhauser, Mingqi Wu, Fanny Yang
Poster
Thu 21:00 Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
Tianyu Ding, Zhihui Zhu, Rene Vidal, Daniel Robinson
Poster
Thu 21:00 Active Slices for Sliced Stein Discrepancy
Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jose Miguel Hernandez-Lobato
Poster
Thu 21:00 Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
Poster
Thu 21:00 Efficient Online Learning for Dynamic k-Clustering
Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis
Poster
Thu 21:00 CountSketches, Feature Hashing and the Median of Three
Kasper Green Larsen, Rasmus Pagh, Jakub Tětek
Poster
Thu 21:00 Meta-Thompson Sampling
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari
Poster
Thu 21:00 Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh
Poster
Thu 21:00 Average-Reward Off-Policy Policy Evaluation with Function Approximation
Shangtong Zhang, Yi Wan, Richard Sutton, Shimon Whiteson
Poster
Thu 21:00 Few-shot Language Coordination by Modeling Theory of Mind
Hao Zhu, Graham Neubig, Yonatan Bisk
Poster
Thu 21:00 GBHT: Gradient Boosting Histogram Transform for Density Estimation
Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin
Poster
Thu 21:00 Discretization Drift in Two-Player Games
Mihaela Rosca, Yan Wu, Benoit Dherin, David GT Barrett
Poster
Thu 21:00 Testing Group Fairness via Optimal Transport Projections
Nian Si, Karthyek Murthy, Jose Blanchet, Viet Anh Nguyen
Poster
Thu 21:00 Label Inference Attacks from Log-loss Scores
Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Seyi Feyisetan, Nathanael Teissier
Poster
Thu 21:00 Probabilistic Generating Circuits
Honghua Zhang, Brendan Juba, Guy Van den Broeck
Poster
Thu 21:00 Elementary superexpressive activations
Dmitry Yarotsky
Poster
Thu 21:00 Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
Poster
Thu 21:00 A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Workshop
Fri 5:00 Theory and Foundation of Continual Learning
Thang Doan, Bogdan Mazoure, Amal Rannen Triki, Rahaf Aljundi, Vincenzo Lomonaco, Xu He, Arslan Chaudhry Chaudhry
Workshop
Fri 7:00 Theory and Practice of Differential Privacy
Rachel Cummings, Gautam Kamath
Workshop
Sat 6:00 Subset Selection in Machine Learning: From Theory to Applications
Rishabh Lyer, Abir De, Ganesh Ramakrishnan, Jeff Bilmes
Workshop
Sat 7:00 Information-Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning (ITR3)
Ahmad Beirami, Flavio Calmon, Berivan Isik, Haewon Jeong, Matthew Nokleby, Cynthia Rush
Workshop
Sat 7:00 Beyond first-order methods in machine learning systems
Albert S Berahas, Tasos Kyrillidis, Fred Roosta, Amir Gholaminejad, Michael Mahoney, Rachael Tappenden, Raghu Bollapragada, Rixon Crane, J. Lyle Kim
Workshop
Sat 8:45 Time Series Workshop
Yian Ma, Ehi Nosakhare, Yuyang Wang, Scott Yang, Rose Yu
Workshop
Sat 9:00 Workshop on Reinforcement Learning Theory
Shipra Agrawal, Simon Du, Niao He, Csaba Szepesvari, Lin Yang
Workshop
Sat 10:00 Sparsity in the Partially Controllable LQR
Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
Workshop
Sat 10:00 The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning
Mikhail Belkin
Workshop
Sat 10:15 On the Theory of Reinforcement Learning with Once-per-Episode Feedback
Niladri Chatterji, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Workshop
Sat 10:15 SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality
Courtney Paquette
Workshop
Sat 10:50 Aaron Roth. Better Estimates of Prediction Uncertainty
Workshop
Sat 11:30 Theory of feature selection
Rajiv Khanna
Workshop
Sat 11:50 Theory of feature selection Live Q&A
Workshop
Sat 12:04 Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Workshop
Sat 14:50 A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck, Mark Sellke
Workshop
Sat 15:40 An Extreme Point Approach to Subset Selection
Viveck Cadambe, Bill Kay
Workshop
Sat 16:33 Understanding the Under-Coverage Bias in Uncertainty Estimation (Spotlight #8)
Yu Bai
Workshop
Learning under Distribution Mismatch and Model Misspecification
Mohammad Saeed Masiha, Mohammad Reza Aref
Workshop
Sliced Mutual Information: A Scalable Measure of Statistical Dependence
Ziv Goldfeld, Kristjan Greenewald
Workshop
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel Rodrigues, Gregory Wornell
Workshop
Sub-population Guarantees for Importance Weights and KL-Divergence Estimation
Parikshit Gopalan, Nina Narodytska, Omer Reingold, Vatsal Sharan, Udi Wieder
Workshop
Multistage stepsize schedule in Federated Learning: Bridging Theory and Practice
Workshop
Optimal Accounting of Differential Privacy via Characteristic Function
Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang
Workshop
Outlier-Robust Optimal Transport with Applications to Generative Modeling and Data Privacy
Sloan Nietert, Rachel Cummings, Ziv Goldfeld
Workshop
On the Convergence of Deep Learning with Differential Privacy
Woody Bu, Hua Wang, Qi Long, Weijie Su
Workshop
Adaptive Machine Unlearning
Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites
Workshop
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal
Workshop
Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Workshop
An Extreme Point Approach to Subset Selection
Viveck Cadambe, Bill Kay
Workshop
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations
Ziquan Liu, Yufei Cui, Antoni Chan
Workshop
Adversarial Sample Detection via Channel Pruning
Zuohui Chen, RenXuan Wang, Yao Lu, jingyang Xiang, Qi Xuan
Workshop
Differentially Private Classification via 0-1 Loss
Ryan McKenna
Workshop
A Practical Notation for Information-Theoretic Quantities between Outcomes and Random Variables
Andreas Kirsch, Yarin Gal
Workshop
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses
Keegan Harris, Daniel Ngo, Logan Stapleton, Hoda Heidari, Steven Wu
Workshop
On the interplay between data structure and loss function: an analytical study of generalization for classification
Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli
Workshop
How does Over-Parametrization Lead to Acceleration for Learning a Single Teacher Neuron with Quadratic Activation?
Jun-Kun Wang, Jake Abernethy
Workshop
Robust Generalization of Quadratic Neural Networks via Function Identification
Kan Xu, Hamsa Bastani, Osbert Bastani
Workshop
On the Sparsity of Deep Neural Networks in the Overparameterized Regime: An Empirical Study
Rahul Parhi, Jack Wolf, Robert Nowak
Workshop
Epoch-Wise Double Descent: A Theory of Multi-scale Feature Learning Dynamics
Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie
Workshop
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki, Oumar Kaba, Yoshua Bengio, Aaron Courville, Doina Precup, Guillaume Lajoie
Workshop
Overfitting of Polynomial Regression with Overparameterization
Hugo Fabregues, Berfin Simsek
Workshop
A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck, Mark Sellke
Workshop
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage
Jonathan Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun
Workshop
Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks
Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
Workshop
Sparsity in the Partially Controllable LQR
Yonathan Efroni, Sham Kakade, Akshay Krishnamurthy, Cyril Zhang
Workshop
Collision Resolution in Multi-player Bandits Without Observing Collision Information
Eleni Nisioti, Nikolaos Thomos, Boris Bellalta, Anders Jonsson
Workshop
Revisiting Design Choices in Offline Model Based Reinforcement Learning
Cong Lu, Philip Ball, Jack Parker-Holder, Michael A Osborne, Stephen Roberts
Workshop
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
Chi Jin, Qinghua Liu, Tiancheng Yu
Workshop
PreferenceNet: Encoding Human Preferences in Auction Design
Neehar Peri, Michael Curry, Samuel Dooley, John P Dickerson
Workshop
Statistical Inference with M-Estimators on Adaptively Collected Data
Kelly Zhang, Lucas Janson, Susan Murphy
Workshop
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Workshop
Model-based Offline Reinforcement Learning with Local Misspecification
Kefan Dong, Ramtin Keramati, Emma Brunskill
Workshop
ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind
Yuanfei Wang, Fangwei Zhong, Jing Xu, Yizhou Wang
Workshop
Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces
Athina Nisioti, Dario Pavllo, Jonas Kohler
Workshop
On the Theory of Reinforcement Learning with Once-per-Episode Feedback
Niladri Chatterji, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Workshop
Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets
Yue Gao, Pablo Hernandez-Leal, Kry Yik Chau Lui
Workshop
MetaDataset: A Dataset of Datasets for Evaluating Distribution Shifts and Training Conflicts
Weixin Liang, James Zou, Weixin Liang