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Coffee and Check In
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Opening Remarks
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Constant Regret in Exchangeable Action Models: Overbooking, Bin Packing, and Beyond

Daniel Freund (MIT)
Video
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Coffee Break
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Stochastic Bin Packing with Time-Varying Item Sizes

Weina Wang (Carnegie Mellon University)
Video
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Lunch
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A Tutorial on Finite-Sample Guarantees of Contractive Stochastic Approximation With Applications in Reinforcement Learning

Siva Theja Maguluri (Georgia Institute of Technology)
Video
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Coffee Break
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A Tutorial on Finite-Sample Guarantees of Contractive Stochastic Approximation With Applications in Reinforcement Learning

Zaiwei Chen (Caltech)
Video
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Reception (In conjunction with the Peter Bartlett recognition event)
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Coffee and Check In
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The Statistical Complexity of Interactive Decision Making

Dylan Foster (Microsoft Research)
Video
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Break
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A Game-Theoretic Approach to Offline Reinforcement Learning

Ching-An Cheng (Microsoft Research)
Video
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Lunch
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Are Multicriteria MDPs Harder to Solve Than Single-Criteria MDPs?

Csaba Szepasvari (University of Alberta, Google DeepMind)
Video
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Break
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Learning Across Bandits in High Dimension via Robust Statistics

Hamsa Bastani (University of Pennsylvania)
Video
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Coffee and Check In
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Fast Algorithms for Online Stochastic Convex Programming

Nikhil Devanur (Amazon)
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Break
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New Results on Primal-Dual Algorithms for Online Allocation Problems With Applications to Budget Pacing in Online Advertising

Haihao Lu (Chicago Booth School of Business)
Video
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Lunch
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Dynamic Spatial Matching and Applications

Yash Kanoria (Columbia University)
Video
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Break
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Poster Session (In-Person Only)
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Coffee and Check In
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Optimal Learning for Structured Bandits

Negin Golrezei (Massachusetts Institute of Technology)
Video
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Break
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When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications

Rad Niazadeh (The University of Chicago Booth School of Business)
Video
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Lunch
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The Power of Adaptivity in Representation Learning: From Meta-Learning to Federated Learning

Sanjay Shakkottai (University of Texas at Austin)
Video
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Break
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Open Problem Session (In-Person Only)
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Coffee and Check In
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Near-Optimal No-Regret Learning for General Convex Games

Gabriele Farina (Carnegie Mellon University)
Video
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Break
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Learning to Control Safety-Critical Systems

Adam Wierman (California Institute of Technology)
Video