Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes

12 December 2022

Quanquan Gu

Papers citing "Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes"

47 / 47 papers shown

Title
Towards Optimal Differentially Private Regret Bounds in Linear MDPs Sharan Sahu 55 0 0 12 Apr 2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism Harin Lee Min-hwan Oh OffRL 59 0 0 02 Mar 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Chenlu Ye Yujia Jin Alekh Agarwal Tong Zhang 98 0 0 04 Feb 2025
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation Long-Fei Li Yu-Jie Zhang Peng Zhao Zhi-Hua Zhou 92 4 0 17 Jan 2025
Efficient, Low-Regret, Online Reinforcement Learning for Linear MDPs Philips George John Arnab Bhattacharyya Silviu Maniu Dimitrios Myrisiotis Zhenan Wu OffRL 31 0 0 16 Nov 2024
Robust Thompson Sampling Algorithms Against Reward Poisoning Attacks Yinglun Xu Zhiwei Wang Gagandeep Singh AAML 23 0 0 25 Oct 2024
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span Woojin Chae Kihyuk Hong Yufan Zhang Ambuj Tewari Dabeen Lee 32 1 0 19 Oct 2024
Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning Zhishuai Liu Weixin Wang Pan Xu 33 1 0 30 Sep 2024
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs Kevin Tan Wei Fan Yuting Wei OffRL 69 2 0 08 Aug 2024
Multiple Greedy Quasi-Newton Methods for Saddle Point Problems Minheng Xiao Shi Bo Zhizhong Wu 28 5 0 01 Aug 2024
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation Taehyun Cho Seung Han Kyungjae Lee Seokhun Ju Dohyeong Kim Jungwoo Lee 64 0 0 31 Jul 2024
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes Asaf B. Cassel Aviv A. Rosenberg 35 1 0 03 Jul 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions Noah Golowich Ankur Moitra OffRL 30 1 0 17 Jun 2024
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs Kihyuk Hong Yufan Zhang Ambuj Tewari Dabeen Lee Ambuj Tewari 34 2 0 23 May 2024
Imitation Learning in Discounted Linear MDPs without exploration assumptions Luca Viano Stratis Skoulakis V. Cevher 30 3 0 03 May 2024
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation Jianliang He Han Zhong Zhuoran Yang 38 6 0 19 Apr 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm Miao Lu Han Zhong Tong Zhang Jose H. Blanchet OffRL OOD 73 4 0 04 Apr 2024
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes He Wang Laixi Shi Yuejie Chi OffRL 36 6 0 19 Mar 2024
Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang Jason D. Lee Yuxin Chen Simon S. Du 33 3 0 15 Mar 2024
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation Zhishuai Liu Pan Xu OOD OffRL 39 8 0 23 Feb 2024
Reinforcement Learning from Human Feedback with Active Queries Kaixuan Ji Jiafan He Quanquan Gu 13 17 0 14 Feb 2024
Sample Complexity Characterization for Linear Contextual MDPs Junze Deng Yuan-Chia Cheng Shaofeng Zou Yingbin Liang 30 1 0 05 Feb 2024
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints Dan Qiao Yu-Xiang Wang OffRL 24 3 0 02 Feb 2024
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees Toshinori Kitamura Tadashi Kozuno Masahiro Kato Yuki Ichihara Soichiro Nishimori Akiyoshi Sannai Sho Sonoda Wataru Kumagai Yutaka Matsuo 37 2 0 31 Jan 2024
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback Canzhe Zhao Ruofeng Yang Baoxiang Wang Xuezhou Zhang Shuai Li 22 2 0 14 Nov 2023
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation Nikki Lijing Kuang Ming Yin Mengdi Wang Yu-Xiang Wang Yian Ma 24 6 0 29 Oct 2023
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning Qiwei Di Heyang Zhao Jiafan He Quanquan Gu OffRL 53 5 0 02 Oct 2023
Minimax Optimal Q Learning with Nearest Neighbors Puning Zhao Lifeng Lai OffRL 49 10 0 03 Aug 2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback Yu Chen Yihan Du Pihe Hu Si-Yi Wang De-hui Wu Longbo Huang 24 6 0 06 Jul 2023
On the Model-Misspecification in Reinforcement Learning Yunfan Li Lin F. Yang 36 5 0 19 Jun 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 22 6 0 12 Jun 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 26 20 0 29 May 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice Toshinori Kitamura Tadashi Kozuno Yunhao Tang Nino Vieillard Michal Valko ... Olivier Pietquin M. Geist Csaba Szepesvári Wataru Kumagai Yutaka Matsuo OffRL 30 2 0 22 May 2023
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL Qinghua Liu Gellert Weisz András Gyorgy Chi Jin Csaba Szepesvári OffRL 21 8 0 18 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 30 26 0 15 May 2023
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs Kaixuan Ji Qingyue Zhao Jiafan He Weitong Zhang Q. Gu 47 4 0 15 May 2023
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation Yifei Min Jiafan He Tianhao Wang Quanquan Gu 38 7 0 10 May 2023
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs Junkai Zhang Weitong Zhang Quanquan Gu 27 3 0 17 Mar 2023
Variance-aware robust reinforcement learning with linear function approximation under heavy-tailed rewards Xiang Li Qiang Sun 24 8 0 09 Mar 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency Heyang Zhao Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 24 27 0 21 Feb 2023
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang-yuan Kong Xiangcheng Zhang Baoxiang Wang Shuai Li 13 12 0 14 Feb 2023
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation Pihe Hu Yu Chen Longbo Huang 6 34 0 23 Jun 2022
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs Dongruo Zhou Quanquan Gu 73 43 0 23 May 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 61 46 0 13 May 2022
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 63 36 0 29 Jan 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 112 166 0 06 Jan 2021
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 132 135 0 09 Dec 2019