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05/10/2023
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
We study multi-agent reinforcement learning in the setting of episodic M...
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04/06/2023
Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts
Integrating high-level semantically correlated contents and low-level an...
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04/05/2023
ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast
Medical data often exhibits long-tail distributions with heavy class imb...
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02/03/2023
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
For medical image segmentation, contrastive learning is the dominant pra...
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07/07/2022
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
We study federated contextual linear bandits, where M agents cooperate w...
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05/26/2022
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
We study offline reinforcement learning (RL) in partially observable Mar...
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03/07/2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets
We study a Markov matching market involving a planner and a set of strat...
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10/25/2021
Learning Stochastic Shortest Path with Linear Function Approximation
We study the stochastic shortest path (SSP) problem in reinforcement lea...
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06/22/2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation
We study the off-policy evaluation (OPE) problem in reinforcement learni...
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08/03/2020
Multiple Descent: Design Your Own Generalization Curve
This paper explores the generalization loss of linear regression in vari...
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02/25/2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization
Despite remarkable success, deep neural networks are sensitive to human-...
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02/11/2020
