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Provably Efficient Reinforcement Learning with Linear Function Approximation

11 July 2019

Papers citing "Provably Efficient Reinforcement Learning with Linear Function Approximation"

50 / 417 papers shown

Title
Low-Rank MDPs with Continuous Action Spaces Andrew Bennett Nathan Kallus Miruna Oprescu 73 2 0 06 Nov 2023
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning Ahmadreza Moradipari M. Pedramfar Modjtaba Shokrian Zini Vaneet Aggarwal 74 5 0 30 Oct 2023
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning Zhaoyi Zhou Chuning Zhu Runlong Zhou Qiwen Cui Abhishek Gupta S. S. Du OffRL 82 9 0 30 Oct 2023
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation Nikki Lijing Kuang Ming Yin Mengdi Wang Yu Wang Yian Ma 102 6 0 29 Oct 2023
Weakly Coupled Deep Q-Networks Ibrahim El Shar Daniel R. Jiang 72 4 0 28 Oct 2023
Unsupervised Behavior Extraction via Random Intent Priors Haotian Hu Yiqin Yang Jianing Ye Ziqing Mai Chongjie Zhang OffRL 81 9 0 28 Oct 2023
Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage Kishan Panaganti Zaiyan Xu D. Kalathil Mohammad Ghavamzadeh OOD OffRL 83 8 0 27 Oct 2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $ε$ -Greedy Exploration Shuai Zhang Hongkang Li Meng Wang Miao Liu Pin-Yu Chen Songtao Lu Sijia Liu K. Murugesan Subhajit Chaudhury 111 22 0 24 Oct 2023
A Doubly Robust Approach to Sparse Reinforcement Learning Wonyoung Hedge Kim Garud Iyengar A. Zeevi 79 3 0 23 Oct 2023
Corruption-Robust Offline Reinforcement Learning with General Function Approximation Chen Ye Rui Yang Quanquan Gu Tong Zhang OffRL 102 22 0 23 Oct 2023
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback Haolin Liu Chen-Yu Wei Julian Zimmert 78 6 0 17 Oct 2023
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning Parvin Malekzadeh Ming Hou Konstantinos N. Plataniotis 102 1 0 16 Oct 2023
Sample Complexity of Preference-Based Nonparametric Off-Policy Evaluation with Deep Networks Zihao Li Xiang Ji Minshuo Chen Mengdi Wang OffRL 81 0 0 16 Oct 2023
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning Mirco Mutti Ric De Santi Marcello Restelli Alexander Marx Giorgia Ramponi CML 54 4 0 11 Oct 2023
Sample-Efficient Multi-Agent RL: An Optimization Perspective Nuoya Xiong Zhihan Liu Zhaoran Wang Zhuoran Yang 95 1 0 10 Oct 2023
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms Akifumi Wachi Wataru Hashimoto Xun Shen Kazumune Hashimoto 79 11 0 05 Oct 2023
On Representation Complexity of Model-based and Model-free Reinforcement Learning Hanlin Zhu Baihe Huang Stuart Russell OffRL 84 4 0 03 Oct 2023
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning Qiwei Di Heyang Zhao Jiafan He Quanquan Gu OffRL 115 5 0 02 Oct 2023
Bayesian Design Principles for Frequentist Sequential Learning Yunbei Xu A. Zeevi 125 13 0 01 Oct 2023
Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness Xiaoyu Wen Xudong Yu Rui Yang Chenjia Bai Zhen Wang OffRL OnRL 81 10 0 29 Sep 2023
Tempo Adaptation in Non-stationary Reinforcement Learning Hyunin Lee Yuhao Ding Jongmin Lee Ming Jin Javad Lavaei Somayeh Sojoudi 79 3 0 26 Sep 2023
Representation Learning in Low-rank Slate-based Recommender Systems Yijia Dai Wen Sun OffRL 58 0 0 10 Sep 2023
Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning Yong Lin Chen Liu Chen Ye Qing Lian Yuan Yao Tong Zhang 110 5 0 05 Sep 2023
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes Qinbo Bai Washim Uddin Mondal Vaneet Aggarwal 59 13 0 05 Sep 2023
Rate-Optimal Policy Optimization for Linear Markov Decision Processes Uri Sherman Alon Cohen Tomer Koren Yishay Mansour 104 7 0 28 Aug 2023
Learning Optimal Admission Control in Partially Observable Queueing Networks Jonatha Anselmi B. Gaujal Louis-Sébastien Rebuffi 60 1 0 04 Aug 2023
Minimax Optimal Q Learning with Nearest Neighbors Puning Zhao Lifeng Lai OffRL 100 12 0 03 Aug 2023
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation Ruida Zhou Tao-Wen Liu Min Cheng D. Kalathil P. R. Kumar Chao Tian 104 25 0 17 Jul 2023
The complexity of non-stationary reinforcement learning Christos H. Papadimitriou Binghui Peng 52 3 0 13 Jul 2023
Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing Sanae Amani Khushbu Pahwa samani Lin F. Yang LRM 40 1 0 11 Jul 2023
Efficient Model-Free Exploration in Low-Rank MDPs Zakaria Mhammedi Adam Block Dylan J. Foster Alexander Rakhlin OffRL 98 14 0 08 Jul 2023
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight Jiacheng Guo Minshuo Chen Haiquan Wang Caiming Xiong Mengdi Wang Yu Bai 95 5 0 06 Jul 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 82 8 0 06 Jul 2023
Stability of Q-Learning Through Design and Optimism Sean P. Meyn 91 10 0 05 Jul 2023
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 130 5 0 01 Jul 2023
TD Convergence: An Optimization Perspective Kavosh Asadi Shoham Sabach Yao Liu Omer Gottesman Rasool Fakoor MU 88 8 0 30 Jun 2023
Is RLHF More Difficult than Standard RL? Yuanhao Wang Qinghua Liu Chi Jin OffRL 112 67 0 25 Jun 2023
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards Semih Cayci A. Eryilmaz 69 2 0 20 Jun 2023
On the Model-Misspecification in Reinforcement Learning Yunfan Li Lin F. Yang 106 5 0 19 Jun 2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions Nishil Patel Sebastian Lee Stefano Sarao Mannelli Sebastian Goldt Adrew Saxe OffRL 136 4 0 17 Jun 2023
Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling Yunfan Li Yiran Wang Y. Cheng Lin F. Yang OffRL 104 4 0 15 Jun 2023
Theoretical Hardness and Tractability of POMDPs in RL with Partial Online State Information Ming Shi Yingbin Liang Ness B. Shroff 82 2 0 14 Jun 2023
Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources Chengshuai Shi Wei Xiong Cong Shen Jing Yang OffRL 77 3 0 14 Jun 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds Sattar Vakili Julia Olkhovskaya 103 9 0 13 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 83 10 0 12 Jun 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 57 6 0 12 Jun 2023
A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs Mikael Henaff Minqi Jiang Roberta Raileanu 90 13 0 05 Jun 2023
High-probability sample complexities for policy evaluation with linear function approximation Gen Li Weichen Wu Yuejie Chi Cong Ma Alessandro Rinaldo Yuting Wei OffRL 106 7 0 30 May 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 124 22 0 29 May 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 116 23 0 29 May 2023