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Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP


Dec 01, 2022
Jinghan Wang, Mengdi Wang, Lin F. Yang

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Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms


Nov 08, 2022
Osama A. Hanna, Lin F. Yang, Christina Fragouli

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Near-Optimal Sample Complexity Bounds for Constrained MDPs


Jun 13, 2022
Sharan Vaswani, Lin F. Yang, Csaba Szepesvári

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Learning in Distributed Contextual Linear Bandits Without Sharing the Context


Jun 08, 2022
Osama A. Hanna, Lin F. Yang, Christina Fragouli

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Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximation


Jun 01, 2022
Sanae Amani, Lin F. Yang, Ching-An Cheng

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Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost


May 26, 2022
Sanae Amani, Tor Lattimore, András György, Lin F. Yang

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Solving Multi-Arm Bandit Using a Few Bits of Communication


Nov 11, 2021
Osama A. Hanna, Lin F. Yang, Christina Fragouli

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Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning


Nov 01, 2021
Yuanzhi Li, Ruosong Wang, Lin F. Yang

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Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs


Oct 26, 2021
Han Zhong, Jiayi Huang, Lin F. Yang, Liwei Wang

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* NeurIPS 2021 

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Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration


Oct 12, 2021
Weichao Mao, Tamer Başar, Lin F. Yang, Kaiqing Zhang

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