215 Results

Expo Talk Panel
Sun 0:15 Machine Learning for Drug Discovery in the era of SARS-CoV-2. A panel discussion
Mary Ellen Perry
Poster
Tue 7:00 Customizing ML Predictions for Online Algorithms
Keerti Anand, Rong Ge, Debmalya Panigrahi
Poster
Tue 7:00 Familywise Error Rate Control by Interactive Unmasking
Boyan Duan, Aaditya Ramdas, Larry Wasserman
Poster
Tue 7:00 Stochastic Regret Minimization in Extensive-Form Games
Gabriele Farina, Christian Kroer, Tuomas Sandholm
Poster
Tue 7:00 Tensor denoising and completion based on ordinal observations
Chanwoo Lee, Miaoyan Wang
Poster
Tue 7:00 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
Chaosheng Dong, Bo Zeng
Poster
Tue 7:00 Maximum-and-Concatenation Networks
Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin
Poster
Tue 7:00 Asynchronous Coagent Networks
James Kostas, Chris Nota, Philip Thomas
Poster
Tue 7:00 Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study
Tanner Fiez, Benjamin Chasnov, Lillian Ratliff
Poster
Tue 7:00 Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension
Yuandong Tian
Poster
Tue 7:00 Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
shuai zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
Poster
Tue 7:00 Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Pranjal Awasthi, Natalie Frank, Mehryar Mohri
Poster
Tue 7:00 Data Amplification: Instance-Optimal Property Estimation
Yi Hao, Alon Orlitsky
Poster
Tue 7:00 On the Noisy Gradient Descent that Generalizes as SGD
Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu
Poster
Tue 7:00 Towards Understanding the Dynamics of the First-Order Adversaries
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie Su
Poster
Tue 7:00 Reverse-engineering deep ReLU networks
David Rolnick, Konrad Kording
Poster
Tue 7:00 Provably Efficient Exploration in Policy Optimization
Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang
Poster
Tue 7:00 From Importance Sampling to Doubly Robust Policy Gradient
Jiawei Huang, Nan Jiang
Poster
Tue 7:00 Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
Prashanth L.A., Krishna Jagannathan, Ravi Kolla
Poster
Tue 8:00 Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Wu
Poster
Tue 8:00 Strategyproof Mean Estimation from Multiple-Choice Questions
Anson Kahng, Gregory Kehne, Ariel Procaccia
Poster
Tue 8:00 Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc Bellemare
Poster
Tue 8:00 Estimating the Number and Effect Sizes of Non-null Hypotheses
Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson
Poster
Tue 8:00 Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang, Cengiz Pehlevan
Poster
Tue 8:00 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique, Paul Weng, Matthieu Zimmer
Poster
Tue 8:00 Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition
Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu
Poster
Tue 8:00 Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir, Kamil Ciosek
Poster
Tue 8:00 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
Shangtong Zhang, Bo Liu, Shimon Whiteson
Poster
Tue 8:00 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
Chiru Bhattacharyya, Ravindran Kannan
Poster
Tue 9:00 Learning and Sampling of Atomic Interventions from Observations
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, Vinodchandran N. Variyam
Poster
Tue 9:00 Neural Contextual Bandits with UCB-based Exploration
Dongruo Zhou, Lihong Li, Quanquan Gu
Poster
Tue 9:00 Tightening Exploration in Upper Confidence Reinforcement Learning
Hippolyte Bourel, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi
Poster
Tue 9:00 Context Aware Local Differential Privacy
Jayadev Acharya, Kallista Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun
Poster
Tue 9:00 Provable guarantees for decision tree induction: the agnostic setting
Guy Blanc, Jane Lange, Li-Yang Tan
Poster
Tue 9:00 Low-loss connection of weight vectors: distribution-based approaches
Ivan Anokhin, Dmitry Yarotsky
Poster
Tue 9:00 Deep k-NN for Noisy Labels
Dara Bahri, Heinrich Jiang, Maya Gupta
Poster
Tue 9:00 Structured Policy Iteration for Linear Quadratic Regulator
Youngsuk Park, Ryan A. Rossi, Zheng Wen, Gang Wu, Handong Zhao
Poster
Tue 9:00 Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal, Arya Mazumdar
Poster
Tue 9:00 Disentangling Trainability and Generalization in Deep Neural Networks
Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz
Poster
Tue 9:00 Fiduciary Bandits
Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz
Poster
Tue 10:00 Logarithmic Regret for Adversarial Online Control
Dylan Foster, Max Simchowitz
Poster
Tue 10:00 A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
Nikunj Saunshi, Yi Zhang, Misha Khodak, Sanjeev Arora
Poster
Tue 10:00 On Learning Sets of Symmetric Elements
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
Poster
Tue 10:00 Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning
Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
Poster
Tue 10:00 Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning
Amin Rakhsha, Goran Radanovic, Rati Devidze, Jerry Zhu, Adish Singla
Poster
Tue 10:00 When are Non-Parametric Methods Robust?
Robi Bhattacharjee, Kamalika Chaudhuri
Poster
Tue 10:00 Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models
Yiding Feng, Ekaterina Khmelnitskaya, Denis Nekipelov
Poster
Tue 10:00 Harmonic Decompositions of Convolutional Networks
Meyer Scetbon, Zaid Harchaoui
Poster
Tue 10:00 Federated Learning with Only Positive Labels
Felix Xinnan Yu, Ankit Singh Rawat, Aditya Menon, Sanjiv Kumar
Poster
Tue 10:00 Explainable k-Means and k-Medians Clustering
Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost
Poster
Tue 11:00 Information-Theoretic Local Minima Characterization and Regularization
Zhiwei Jia, Hao Su
Poster
Tue 11:00 Consistent Structured Prediction with Max-Min Margin Markov Networks
Alex Nowak, Francis Bach, Alessandro Rudi
Poster
Tue 11:00 Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma
Poster
Tue 11:00 Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer
Alexey Drutsa
Poster
Tue 11:00 When Explanations Lie: Why Many Modified BP Attributions Fail
Leon Sixt, Maximilian Granz, Tim Landgraf
Poster
Tue 11:00 Understanding and Mitigating the Tradeoff between Robustness and Accuracy
Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang
Poster
Tue 11:00 Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain
Poster
Tue 12:00 Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay
REDA ALAMI, Odalric-Ambrym Maillard, Raphaël Féraud
Poster
Tue 12:00 Constructive Universal High-Dimensional Distribution Generation through Deep ReLU Networks
Dmytro Perekrestenko, Stephan Müller, Helmut Bölcskei
Poster
Tue 12:00 Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
Yao Liu, Pierre-Luc Bacon, Emma Brunskill
Poster
Tue 13:00 The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture
Francesca Mignacco, Florent Krzakala, Yue Lu, Pierfrancesco Urbani, Lenka Zdeborova
Poster
Tue 13:00 Near-Tight Margin-Based Generalization Bounds for Support Vector Machines
Allan Grønlund, Lior Kamma, Kasper Green Larsen
Poster
Tue 13:00 Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?
Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
Poster
Tue 13:00 Learning with Good Feature Representations in Bandits and in RL with a Generative Model
Tor Lattimore, Csaba Szepesvari, Gellért Weisz
Poster
Tue 13:00 Supervised learning: no loss no cry
Richard Nock, Aditya Menon
Poster
Tue 13:00 Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gurbuzbalaban
Poster
Tue 14:00 Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain COUILLET
Poster
Tue 14:00 Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation
Reinhard Heckel, Mahdi Soltanolkotabi
Poster
Tue 14:00 Infinite attention: NNGP and NTK for deep attention networks
Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak
Poster
Tue 14:00 Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently
Asaf Cassel, Alon Cohen, Tomer Koren
Poster
Tue 14:00 Decentralised Learning with Random Features and Distributed Gradient Descent
Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco
Poster
Tue 14:00 Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure
John Sipple
Poster
Tue 14:00 Optimal Estimator for Unlabeled Linear Regression
Hang Zhang, Ping Li
Poster
Tue 15:00 Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Poster
Tue 15:00 Thompson Sampling Algorithms for Mean-Variance Bandits
Qiuyu Zhu, Vincent Tan
Poster
Tue 15:00 Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation
Nathan Kallus, Masatoshi Uehara
Poster
Tue 18:00 Efficiently Learning Adversarially Robust Halfspaces with Noise
Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nati Srebro
Poster
Tue 18:00 Logistic Regression for Massive Data with Rare Events
HaiYing Wang
Poster
Wed 5:00 On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies
Hengrui Cai, Wenbin Lu, Rui Song
Poster
Wed 5:00 On Learning Language-Invariant Representations for Universal Machine Translation
Han Zhao, Junjie Hu, Andrej Risteski
Poster
Wed 5:00 Optimal Bounds between f-Divergences and Integral Probability Metrics
Rohit Agrawal, Thibaut Horel
Poster
Wed 5:00 The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered Smoothers
Pierre C Bellec, Dana Yang
Poster
Wed 5:00 Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Steven Wu
Poster
Wed 5:00 Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
Ruixiang ZHANG, Masanori Koyama, Katsuhiko Ishiguro
Poster
Wed 5:00 Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
Jiaoyang Huang, Horng-Tzer Yau
Poster
Wed 5:00 Learning Opinions in Social Networks
Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang
Poster
Wed 5:00 Adaptive Estimator Selection for Off-Policy Evaluation
Yi Su, Pavithra Srinath, Akshay Krishnamurthy
Poster
Wed 5:00 Abstraction Mechanisms Predict Generalization in Deep Neural Networks
Alex Gain, Hava Siegelmann
Poster
Wed 5:00 On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm
Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui
Poster
Wed 5:00 Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study
Siqiang Luo
Poster
Wed 5:00 InstaHide: Instance-hiding Schemes for Private Distributed Learning
Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora
Poster
Wed 5:00 The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization
Ben Adlam, Jeffrey Pennington
Poster
Wed 5:00 Second-Order Provable Defenses against Adversarial Attacks
Sahil Singla, Soheil Feizi
Poster
Wed 5:00 Eliminating the Invariance on the Loss Landscape of Linear Autoencoders
Reza Oftadeh, Jiayi Shen, Zhangyang Wang, Dylan Shell
Poster
Wed 5:00 Private Query Release Assisted by Public Data
Raef Bassily, Albert Cheu, Shay Moran, Sasho Nikolov, Jonathan Ullman, Steven Wu
Poster
Wed 5:00 Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games
Darren Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael Jordan
Poster
Wed 5:00 Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting
Zixin Zhong, Wang Chi Cheung, Vincent Tan
Poster
Wed 8:00 Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans
Poster
Wed 8:00 Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
Poster
Wed 8:00 Black-box Certification and Learning under Adversarial Perturbations
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Poster
Wed 8:00 Strength from Weakness: Fast Learning Using Weak Supervision
Joshua Robinson, Stefanie Jegelka, Suvrit Sra
Poster
Wed 8:00 Individual Calibration with Randomized Forecasting
Shengjia Zhao, Tengyu Ma, Stefano Ermon
Poster
Wed 8:00 Identifying the Reward Function by Anchor Actions
Sinong Geng, Houssam Nassif, Charlie Manzanares, Max Reppen, Ronnie Sircar
Poster
Wed 8:00 Efficient Policy Learning from Surrogate-Loss Classification Reductions
Andrew Bennett, Nathan Kallus
Poster
Wed 8:00 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
Yunwen Lei, Yiming Ying
Poster
Wed 8:00 Class-Weighted Classification: Trade-offs and Robust Approaches
Neil Xu, Chen Dan, Justin Khim, Pradeep Ravikumar
Poster
Wed 8:00 Understanding Self-Training for Gradual Domain Adaptation
Ananya Kumar, Tengyu Ma, Percy Liang
Poster
Wed 8:00 Sample Amplification: Increasing Dataset Size even when Learning is Impossible
Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant
Poster
Wed 8:00 Approximation Capabilities of Neural ODEs and Invertible Residual Networks
Han Zhang, Xi Gao, Jacob Unterman, Tom Arodz
Poster
Wed 9:00 On the consistency of top-k surrogate losses
Forest Yang, Sanmi Koyejo
Poster
Wed 9:00 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying
Poster
Wed 9:00 Optimization Theory for ReLU Neural Networks Trained with Normalization Layers
Yonatan Dukler, Quanquan Gu, Guido Montufar
Poster
Wed 9:00 Provable Self-Play Algorithms for Competitive Reinforcement Learning
Yu Bai, Chi Jin
Poster
Wed 10:00 Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks
Mert Pilanci, Tolga Ergen
Poster
Wed 10:00 Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
Poster
Wed 10:00 Efficiently Solving MDPs with Stochastic Mirror Descent
Yujia Jin, Aaron Sidford
Poster
Wed 10:00 Provable Representation Learning for Imitation Learning via Bi-level Optimization
Sanjeev Arora, Simon Du, Sham Kakade, Yuping Luo, Nikunj Saunshi
Poster
Wed 10:00 Fast computation of Nash Equilibria in Imperfect Information Games
Remi Munos, Julien Perolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls
Poster
Wed 10:00 The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein
Poster
Wed 10:00 The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons
Wenbo Ren, Jia Liu, Ness Shroff
Poster
Wed 11:00 The Implicit and Explicit Regularization Effects of Dropout
Colin Wei, Sham Kakade, Tengyu Ma
Poster
Wed 11:00 Learning Near Optimal Policies with Low Inherent Bellman Error
Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill
Poster
Wed 11:00 Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Eran Malach, Gilad Yehudai, Shai Shalev-Schwartz, Ohad Shamir
Poster
Wed 11:00 On the Number of Linear Regions of Convolutional Neural Networks
Huan Xiong, Lei Huang, Mengyang Yu, Li Liu, Fan Zhu, Ling Shao
Poster
Wed 11:00 Gamification of Pure Exploration for Linear Bandits
Rémy Degenne, Pierre Menard, Xuedong Shang, Michal Valko
Poster
Wed 11:00 Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime
Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala
Poster
Wed 12:00 Optimal Continual Learning has Perfect Memory and is NP-hard
Jeremias Knoblauch, Hisham Husain, Tom Diethe
Poster
Wed 12:00 Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
Alexey Drutsa
Poster
Wed 12:00 Towards a General Theory of Infinite-Width Limits of Neural Classifiers
Eugene Golikov
Poster
Wed 12:00 No-Regret Exploration in Goal-Oriented Reinforcement Learning
Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric
Poster
Wed 12:00 Unique Properties of Flat Minima in Deep Networks
Rotem Mulayoff, Tomer Michaeli
Poster
Wed 12:00 Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation
Konstantinos Pitas
Poster
Wed 12:00 Training Linear Neural Networks: Non-Local Convergence and Complexity Results
Armin Eftekhari
Poster
Wed 12:00 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
Marc Abeille, Alessandro Lazaric
Poster
Wed 12:00 Curvature-corrected learning dynamics in deep neural networks
Dongsung Huh
Poster
Wed 12:00 Convergence Rates of Variational Inference in Sparse Deep Learning
Badr-Eddine Chérief-Abdellatif
Poster
Wed 13:00 Quantum Boosting
Srinivasan Arunachalam, Reevu Maity
Poster
Wed 13:00 On the Sample Complexity of Adversarial Multi-Source PAC Learning
Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph H. Lampert
Poster
Wed 13:00 Attentive Group Equivariant Convolutional Networks
David Romero, Erik Bekkers, Jakub Tomczak, Mark Hoogendoorn
Poster
Wed 13:00 Generalisation error in learning with random features and the hidden manifold model
Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mezard, Lenka Zdeborova
Poster
Wed 14:00 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia, Haipeng Luo, Hiteshi Sharma, Rahul Jain
Poster
Wed 15:00 Statistically Efficient Off-Policy Policy Gradients
Nathan Kallus, Masatoshi Uehara
Poster
Wed 16:00 Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Poster
Wed 16:00 Boosted Histogram Transform for Regression
Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin
Poster
Wed 16:00 From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics
Sai Ganesh Nagarajan, David Balduzzi, Georgios Piliouras
Poster
Thu 6:00 Does label smoothing mitigate label noise?
Michal Lukasik, Srinadh Bhojanapalli, Aditya Menon, Sanjiv Kumar
Poster
Thu 6:00 Learning the Valuations of a $k$-demand Agent
Hanrui Zhang, Vincent Conitzer
Poster
Thu 6:00 Performative Prediction
Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner, University of California Moritz Hardt
Poster
Thu 6:00 Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming
Daoli Zhu, Lei Zhao
Poster
Thu 6:00 Towards Understanding the Regularization of Adversarial Robustness on Neural Networks
Yuxin Wen, Shuai Li, Kui Jia
Poster
Thu 6:00 Interpreting Robust Optimization via Adversarial Influence Functions
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Poster
Thu 6:00 Sparsified Linear Programming for Zero-Sum Equilibrium Finding
Brian Zhang, Tuomas Sandholm
Poster
Thu 6:00 Do GANs always have Nash equilibria?
Farzan Farnia, Asuman Ozdaglar
Poster
Thu 6:00 Bandits for BMO Functions
Tianyu Wang, Cynthia Rudin
Poster
Thu 6:00 Robust Pricing in Dynamic Mechanism Design
Yuan Deng, Sébastien Lahaie, Vahab Mirrokni
Poster
Thu 6:00 Convex Calibrated Surrogates for the Multi-Label F-Measure
Mingyuan Zhang, Harish Ramaswamy, Shivani Agarwal
Poster
Thu 6:00 Universal Equivariant Multilayer Perceptrons
Siamak Ravanbakhsh
Poster
Thu 6:00 Reward-Free Exploration for Reinforcement Learning
Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu
Poster
Thu 6:00 Low-Rank Bottleneck in Multi-head Attention Models
Srinadh Bhojanapalli, Chulhee (Charlie) Yun, Ankit Singh Rawat, Sashank Jakkam Reddi, Sanjiv Kumar
Poster
Thu 6:00 Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification
Chen Dan, Yuting Wei, Pradeep Ravikumar
Poster
Thu 6:00 On a projective ensemble approach to two sample test for equality of distributions
Zhimei Li, Yaowu Zhang
Poster
Thu 6:00 On the Expressivity of Neural Networks for Deep Reinforcement Learning
Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma
Poster
Thu 6:00 Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon, Abdul Canatar, Cengiz Pehlevan
Poster
Thu 6:00 Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation
Yaqi Duan, Zeyu Jia, Mengdi Wang
Poster
Thu 6:00 Estimation of Bounds on Potential Outcomes For Decision Making
Maggie Makar, Fredrik Johansson, John Guttag, David Sontag
Poster
Thu 6:00 Reducing Sampling Error in Batch Temporal Difference Learning
Brahma Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone
Poster
Thu 6:00 Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
Sudeep Salgia, Qing Zhao, Sattar Vakili
Poster
Thu 6:00 Piecewise Linear Regression via a Difference of Convex Functions
Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama
Poster
Thu 6:00 Improved Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance
Blair Bilodeau, Dylan Foster, Daniel Roy
Poster
Thu 6:00 Black-Box Methods for Restoring Monotonicity
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos
Poster
Thu 6:00 Strategic Classification is Causal Modeling in Disguise
John Miller, Smitha Milli, University of California Moritz Hardt
Poster
Thu 7:00 Uniform Convergence of Rank-weighted Learning
Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar
Poster
Thu 7:00 No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Chara Podimata, Jenn Wortman Vaughan
Poster
Thu 7:00 Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks
Marko Vasic, Cameron Chalk, Sarfraz Khurshid, David Soloveichik
Poster
Thu 7:00 Better depth-width trade-offs for neural networks through the lens of dynamical systems
Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas
Poster
Thu 7:00 Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False
Zehua Lai, Lek-Heng Lim
Poster
Thu 7:00 Generalization via Derandomization
Jeffrey Negrea, Gintare Karolina Dziugaite, Daniel Roy
Poster
Thu 7:00 Lorentz Group Equivariant Neural Network for Particle Physics
Alexander Bogatskiy, Brandon Anderson, Jan T Offermann, Marwah Roussi, David Miller, Risi Kondor
Poster
Thu 7:00 The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation
Zhe Feng, David Parkes, Haifeng Xu
Poster
Thu 7:00 Goodness-of-Fit Tests for Inhomogeneous Random Graphs
Soham Dan, Bhaswar B. Bhattacharya
Poster
Thu 7:00 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Poster
Thu 7:00 ConQUR: Mitigating Delusional Bias in Deep Q-Learning
DiJia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier
Poster
Thu 7:00 Model-Based Reinforcement Learning with Value-Targeted Regression
Alex Ayoub, Zeyu Jia, Csaba Szepesvari, Mengdi Wang, Lin Yang
Poster
Thu 7:00 Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games
Youzhi Zhang, Bo An
Poster
Thu 7:00 Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin Yang, Mengdi Wang
Poster
Thu 7:00 Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model
Ying Jin, Zhaoran Wang, Junwei Lu
Poster
Thu 8:00 Principled learning method for Wasserstein distributionally robust optimization with local perturbations
Yongchan Kwon, Wonyoung Kim, Johann Won, Myunghee Cho Paik
Poster
Thu 8:00 Generalization and Representational Limits of Graph Neural Networks
Vikas K Garg, Stefanie Jegelka, Tommi Jaakkola
Poster
Thu 8:00 Momentum-Based Policy Gradient Methods
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Poster
Thu 8:00 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
Poster
Thu 8:00 High-dimensional Robust Mean Estimation via Gradient Descent
Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
Poster
Thu 8:00 The Performance Analysis of Generalized Margin Maximizers on Separable Data
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
Poster
Thu 8:00 SGD Learns One-Layer Networks in WGANs
Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis
Poster
Thu 9:00 Implicit competitive regularization in GANs
Florian Schaefer, Hongkai Zheng, Anima Anandkumar
Poster
Thu 9:00 On the Global Convergence Rates of Softmax Policy Gradient Methods
Jincheng Mei, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans
Poster
Thu 9:00 A Distributional Framework For Data Valuation
Amirata Ghorbani, Michael Kim, James Zou
Poster
Thu 12:00 Near-optimal Regret Bounds for Stochastic Shortest Path
Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan
Poster
Thu 12:00 Optimistic Bounds for Multi-output Learning
Henry Reeve, Ata Kaban
Poster
Thu 12:00 Extra-gradient with player sampling for faster convergence in n-player games
Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna
Poster
Thu 12:00 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
Alexander Shevchenko, Marco Mondelli
Poster
Thu 12:00 Frequency Bias in Neural Networks for Input of Non-Uniform Density
Ronen Basri, Meirav Galun, Amnon Geifman, David Jacobs, Yoni Kasten, Shira Kritchman
Poster
Thu 12:00 Naive Exploration is Optimal for Online LQR
Max Simchowitz, Dylan Foster
Poster
Thu 12:00 Gradient-free Online Learning in Continuous Games with Delayed Rewards
Amélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou
Poster
Thu 12:00 Topologically Densified Distributions
Christoph Hofer, Florian Graf, Marc Niethammer, Roland Kwitt
Poster
Thu 12:00 Real-Time Optimisation for Online Learning in Auctions
Lorenzo Croissant, Marc Abeille, Clément Calauzènes
Poster
Thu 13:00 Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)
Fabian Hinder, André Artelt, CITEC Barbara Hammer
Poster
Thu 13:00 Teaching with Limited Information on the Learner's Behaviour
Ferdinando Cicalese, Francisco S de Freitas Filho, Eduardo Laber, Marco Molinaro
Poster
Thu 14:00 Optimistic Policy Optimization with Bandit Feedback
Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor
Poster
Thu 15:00 Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness
Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi
Poster
Thu 17:00 More Information Supervised Probabilistic Deep Face Embedding Learning
Ying Huang, Shangfeng Qiu, Wenwei Zhang, Xianghui Luo, Jinzhuo Wang
Poster
Thu 17:00 Minimax Weight and Q-Function Learning for Off-Policy Evaluation
Masatoshi Uehara, Jiawei Huang, Nan Jiang
Poster
Thu 17:00 Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
Poster
Thu 18:00 Few-shot Domain Adaptation by Causal Mechanism Transfer
Takeshi Teshima, Issei Sato, Masashi Sugiyama
Workshop
Fri 6:05 Invited Talk: Christoph H. Lampert "Learning Theory for Continual and Meta-Learning"
Christoph H. Lampert
Workshop
Sat 3:00 Inductive Biases, Invariances and Generalization in Reinforcement Learning
Anirudh Goyal, Rosemary Nan Ke, Jane Wang, Theo Weber, Fabio Viola, Bernhard Schölkopf, Stefan Bauer