Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes

15 December 2020

Quanquan Gu

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

50 / 61 papers shown

Title
Provably Efficient Multi-Objective Bandit Algorithms under Preference-Centric Customization Linfeng Cao Ming Shi Ness B. Shroff 49 0 0 20 Feb 2025
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance S. Iwazaki Shion Takeno 78 1 0 10 Feb 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Chenlu Ye Yujia Jin Alekh Agarwal Tong Zhang 105 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 105 4 0 17 Jan 2025
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits H. Bui Enrique Mallada Anqi Liu 192 0 0 08 Nov 2024
Second Order Bounds for Contextual Bandits with Function Approximation Aldo Pacchiano 61 4 0 24 Sep 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 72 0 0 31 Jul 2024
Imitation Learning in Discounted Linear MDPs without exploration assumptions Luca Viano Stratis Skoulakis V. Cevher 30 3 0 03 May 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 79 6 0 04 Apr 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
Variance-Dependent Regret Bounds for Non-stationary Linear Bandits Zhiyong Wang Jize Xie Yi Chen J. C. Lui Dongruo Zhou 28 0 0 15 Mar 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 42 3 0 28 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 42 2 0 31 Jan 2024
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation Paul Daoudi Mathias Formoso Othman Gaizi Achraf Azize Evrard Garcelon OffRL 26 0 0 24 Dec 2023
Optimal Exploration for Model-Based RL in Nonlinear Systems Andrew Wagenmaker Guanya Shi Kevin G. Jamieson 38 14 0 15 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 30 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 3 0 22 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 35 26 0 15 May 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 28 5 0 22 Feb 2023
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang-yuan Kong Xiangcheng Zhang Baoxiang Wang Shuai Li 26 12 0 14 Feb 2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Volodymyr Tkachuk Seyed Alireza Bakhtiari Johannes Kirschner Matej Jusup Ilija Bogunovic Csaba Szepesvári 32 5 0 08 Feb 2023
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR Kaiwen Wang Nathan Kallus Wen Sun 107 18 0 07 Feb 2023
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments Runlong Zhou Zihan Zhang S. Du 44 10 0 31 Jan 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 32 12 0 30 Jan 2023
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits Subhojyoti Mukherjee Qiaomin Xie Josiah P. Hanna R. Nowak OffRL 53 5 0 29 Jan 2023
Multi-Agent Congestion Cost Minimization With Linear Function Approximations Prashant Trivedi N. Hemachandra 37 0 0 26 Jan 2023
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Yanjun Han OffRL 28 29 0 19 Jan 2023
Near-optimal Policy Identification in Active Reinforcement Learning Xiang Li Viraj Mehta Johannes Kirschner I. Char Willie Neiswanger J. Schneider Andreas Krause Ilija Bogunovic OffRL 43 6 0 19 Dec 2022
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 51 53 0 12 Dec 2022
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Jian Qian Alexander Rakhlin Ayush Sekhari OffRL 38 9 0 25 Nov 2022
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation Thanh Nguyen-Tang Ming Yin Sunil R. Gupta Svetha Venkatesh R. Arora OffRL 58 16 0 23 Nov 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu Lingxiao Wang Chenjia Bai Zhuoran Yang Zhaoran Wang SSL OffRL 26 32 0 29 Jul 2022
Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization Kaixuan Huang Yuehua Wu Xuezhou Zhang Shenyinying Tu Qingyun Wu Mengdi Wang Huazheng Wang 28 1 0 29 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 47 22 0 15 Jun 2022
Offline Reinforcement Learning with Differential Privacy Dan Qiao Yu Wang OffRL 41 23 0 02 Jun 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 66 46 0 13 May 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism Ming Yin Yaqi Duan Mengdi Wang Yu Wang OffRL 34 66 0 11 Mar 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min Tianhao Wang Ruitu Xu Zhaoran Wang Michael I. Jordan Zhuoran Yang 33 21 0 07 Mar 2022
Policy Optimization for Stochastic Shortest Path Liyu Chen Haipeng Luo Aviv A. Rosenberg 19 12 0 07 Feb 2022
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? Han Zhong Zhuoran Yang Zhaoran Wang Michael I. Jordan 31 30 0 27 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 57 11 0 02 Dec 2021
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini Andrea Tirinzoni Aldo Pacchiano Marcello Restelli A. Lazaric Matteo Pirotta 19 18 0 27 Oct 2021
Learning Stochastic Shortest Path with Linear Function Approximation Steffen Czolbe Jiafan He Adrian Dalca Quanquan Gu 39 30 0 25 Oct 2021
Linear Contextual Bandits with Adversarial Corruptions Heyang Zhao Dongruo Zhou Quanquan Gu AAML 36 24 0 25 Oct 2021
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes Chonghua Liao Jiafan He Quanquan Gu 27 17 0 19 Oct 2021
Understanding Domain Randomization for Sim-to-real Transfer Xiaoyu Chen Jiachen Hu Chi Jin Lihong Li Liwei Wang 24 112 0 07 Oct 2021
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination Dylan J. Foster A. Krishnamurthy 48 43 0 05 Jul 2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation Yifei Min Tianhao Wang Dongruo Zhou Quanquan Gu OffRL 37 38 0 22 Jun 2021
Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL Weitong Zhang Jiafan He Dongruo Zhou Amy Zhang Quanquan Gu OffRL 22 11 0 22 Jun 2021