Frequentist Regret Bounds for Randomized Least-Squares Value Iteration

1 November 2019

David Brandfonbrener

Papers citing "Frequentist Regret Bounds for Randomized Least-Squares Value Iteration"

38 / 38 papers shown

Title
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning Yen-Ru Lai Fu-Chieh Chang Pei-Yuan Wu OffRL 81 1 0 22 Aug 2024
Random Latent Exploration for Deep Reinforcement Learning Srinath Mahankali Zhang-Wei Hong Ayush Sekhari Alexander Rakhlin Pulkit Agrawal 35 3 0 18 Jul 2024
Ensemble sampling for linear bandits: small ensembles suffice David Janz A. Litvak Csaba Szepesvári 35 1 0 14 Nov 2023
Dyadic Reinforcement Learning Shuangning Li L. Niell S. Choi Inbal Nahum-Shani Guy Shani Susan Murphy OffRL 25 1 0 15 Aug 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
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang-yuan Kong Xiangcheng Zhang Baoxiang Wang Shuai Li 31 12 0 14 Feb 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 32 12 0 30 Jan 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 7 0 28 Jan 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 51 55 0 12 Dec 2022
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong Han Zhong Chengshuai Shi Cong Shen Tong Zhang 66 18 0 04 Oct 2022
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann M. Mohri Tong Zhang Julian Zimmert OffRL 23 33 0 23 Aug 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 50 22 0 15 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 45 5 0 01 Jun 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback Tiancheng Jin Tal Lancewicki Haipeng Luo Yishay Mansour Aviv A. Rosenberg 74 21 0 31 Jan 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching Gen Li Junbo Li Anmol Kabra Nathan Srebro Zhaoran Wang Zhuoran Yang 37 4 0 28 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 44 30 0 25 Oct 2021
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning Tong Zhang 27 63 0 02 Oct 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 41 93 0 14 Sep 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 31 115 0 19 Aug 2021
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses Haipeng Luo Chen-Yu Wei Chung-Wei Lee 38 44 0 18 Jul 2021
Randomized Exploration for Reinforcement Learning with General Value Function Approximation Haque Ishfaq Qiwen Cui V. Nguyen Alex Ayoub Zhuoran Yang Zhaoran Wang Doina Precup Lin F. Yang 37 43 0 15 Jun 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting Gen Li Yuxin Chen Yuejie Chi Yuantao Gu Yuting Wei OffRL 26 28 0 17 May 2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction Chenjia Bai Lingxiao Wang Lei Han Jianye Hao Animesh Garg Peng Liu Zhaoran Wang OffRL 21 38 0 13 May 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation Andrea Zanette Ching-An Cheng Alekh Agarwal 32 53 0 24 Mar 2021
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs Jiafan He Dongruo Zhou Quanquan Gu 95 24 0 17 Feb 2021
Robust Policy Gradient against Strong Data Corruption Xuezhou Zhang Yiding Chen Xiaojin Zhu Wen Sun AAML 40 37 0 11 Feb 2021
Learning Adversarial Markov Decision Processes with Delayed Feedback Tal Lancewicki Aviv A. Rosenberg Yishay Mansour 43 32 0 29 Dec 2020
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL Andrea Zanette OffRL 26 71 0 14 Dec 2020
Regret Bounds for Adaptive Nonlinear Control Nicholas M. Boffi Stephen Tu Jean-Jacques E. Slotine 41 47 0 26 Nov 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Michael I. Jordan 39 18 0 09 Nov 2020
Efficient Learning in Non-Stationary Linear Markov Decision Processes Ahmed Touati Pascal Vincent 42 29 0 24 Oct 2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 30 18 0 23 Oct 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 36 64 0 18 Aug 2020
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 19 221 0 29 Feb 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie Yudong Chen Zhaoran Wang Zhuoran Yang 39 124 0 17 Feb 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 135 135 0 09 Dec 2019