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Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation

International Conference on Machine Learning (ICML), 2022

23 June 2022

Papers citing "Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation"

27 / 27 papers shown

Title
Influential Bandits: Pulling an Arm May Change the Environment Ryoma Sato Shinji Ito 253 0 0 11 Apr 2025
Demystifying Linear MDPs and Novel Dynamics Aggregation FrameworkInternational Conference on Learning Representations (ICLR), 2024 Joongkyu Lee Min-hwan Oh 163 5 0 31 Oct 2024
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded SpanInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Woojin Chae Kihyuk Hong Yufan Zhang Ambuj Tewari Dabeen Lee 162 1 0 19 Oct 2024
Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning Zhishuai Liu Weixin Wang Pan Xu 318 13 0 30 Sep 2024
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPsNeural Information Processing Systems (NeurIPS), 2024 Kevin Tan Wei Fan Yuting Wei OffRL 262 5 0 08 Aug 2024
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang Boxiang Lyu Delin Qu Mladen Kolar Tong Zhang OffRL 218 1 0 10 Jul 2024
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes Asaf B. Cassel Aviv A. Rosenberg 314 2 0 03 Jul 2024
Sample Complexity Characterization for Linear Contextual MDPs Junze Deng Yuan Cheng Shaofeng Zou Yingbin Liang 155 3 0 05 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 458 4 0 31 Jan 2024
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint Wei Xiong Hanze Dong Chen Ye Ziqi Wang Han Zhong Heng Ji Nan Jiang Tong Zhang OffRL 331 289 0 18 Dec 2023
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information FeedbackNeural Information Processing Systems (NeurIPS), 2023 Canzhe Zhao Ruofeng Yang Baoxiang Wang Xuezhou Zhang Shuai Li 189 4 0 14 Nov 2023
A Doubly Robust Approach to Sparse Reinforcement LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Wonyoung Hedge Kim Garud Iyengar A. Zeevi 167 4 0 23 Oct 2023
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2023 Qiwei Di Heyang Zhao Jiafan He Quanquan Gu OffRL 201 6 0 02 Oct 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret BoundsNeural Information Processing Systems (NeurIPS), 2023 Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 294 11 0 12 Jun 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and PracticeInternational Conference on Machine Learning (ICML), 2023 Toshinori Kitamura Tadashi Kozuno Yunhao Tang Nino Vieillard Michal Valko ... Olivier Pietquin Matthieu Geist Csaba Szepesvári Wataru Kumagai Yutaka Matsuo OffRL 158 4 0 22 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision ProcessesNeural Information Processing Systems (NeurIPS), 2023 Han Zhong Tong Zhang 261 36 0 15 May 2023
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function ApproximationInternational Conference on Machine Learning (ICML), 2023 Yifei Min Jiafan He Tianhao Wang Quanquan Gu 291 10 0 10 May 2023
Variance-aware robust reinforcement learning with linear function approximation under heavy-tailed rewards Xiang Li Qiang Sun 217 9 0 09 Mar 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational EfficiencyAnnual Conference Computational Learning Theory (COLT), 2023 Heyang Zhao Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 239 37 0 21 Feb 2023
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang-yuan Kong Xiangcheng Zhang Baoxiang Wang Shuai Li 186 14 0 14 Feb 2023
Near-optimal Policy Identification in Active Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2022 Xiang Li Viraj Mehta Johannes Kirschner I. Char Willie Neiswanger J. Schneider Andreas Krause Ilija Bogunovic OffRL 157 7 0 19 Dec 2022
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision ProcessesInternational Conference on Machine Learning (ICML), 2022 Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 389 63 0 12 Dec 2022
Near-Optimal Differentially Private Reinforcement LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Dan Qiao Yu Wang 302 16 0 09 Dec 2022
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function ApproximationInternational Conference on Learning Representations (ICLR), 2022 Dan Qiao Yu Wang OffRL 249 15 0 03 Oct 2022
Understanding Deep Neural Function Approximation in Reinforcement Learning via $ε$ -Greedy ExplorationNeural Information Processing Systems (NeurIPS), 2022 Fanghui Liu Luca Viano Volkan Cevher 293 23 0 15 Sep 2022
Online Sub-Sampling for Reinforcement Learning with General Function Approximation Dingwen Kong Ruslan Salakhutdinov Ruosong Wang Lin F. Yang OffRL 187 1 0 14 Jun 2021
Nonstationary Reinforcement Learning with Linear Function Approximation Huozhi Zhou Jinglin Chen Lav Varshney A. Jagmohan 299 31 0 08 Oct 2020