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Dongruo Zhou

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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Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium

Aug 10, 2022
Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan

* 42 pages

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Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs

May 23, 2022
Dongruo Zhou, Quanquan Gu

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* 33 pages, 1 table

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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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Faster Perturbed Stochastic Gradient Methods for Finding Local Minima

Oct 25, 2021
Zixiang Chen, Dongruo Zhou, Quanquan Gu

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* 28 pages, 1 figure, 1 table

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Linear Contextual Bandits with Adversarial Corruptions

Oct 25, 2021
Heyang Zhao, Dongruo Zhou, Quanquan Gu

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* 27 pages, 1 figure

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Iterative Teacher-Aware Learning

Oct 17, 2021
Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu

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* Advances in Neural Information Processing Systems (2021)

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