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Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs


May 15, 2023
Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong Zhang, Quanquan Gu

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* 34 pages 

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Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension


May 15, 2023
Yue Wu, Jiafan He, Quanquan Gu

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* 21 pages, 1 table. To appear in UAI 2023 

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Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation


May 12, 2023
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

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* Published at the 40th International Conference on Machine Learning ( ICML 2023 ) 

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On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits


Mar 16, 2023
Weitong Zhang, Jiafan He, Zhiyuan Fan, Quanquan Gu

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* 28 pages, 2 figures, 2 tables 

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Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency


Feb 21, 2023
Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

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* 43 pages, 2 tables 

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Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes


Dec 12, 2022
Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu

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* 44 pages, 1 table 

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A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits


Jul 07, 2022
Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu

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* 25 pages, 1 figure, 2 tables 

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Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions


May 13, 2022
Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

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* 29 pages, 1 table 

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Bandit Learning with General Function Classes: Heteroscedastic Noise and Variance-dependent Regret Bounds


Feb 28, 2022
Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu

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* 33 pages, 1 table 

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Learning Stochastic Shortest Path with Linear Function Approximation


Oct 25, 2021
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

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* 34 pages, 1 figure 

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