Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound

24 May 2019

Papers citing "Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound"

50 / 94 papers shown

Title
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation Long-Fei Li Yu-Jie Zhang Peng Zhao Zhi-Hua Zhou 108 4 0 17 Jan 2025
Spectral Representation for Causal Estimation with Hidden Confounders Tongzheng Ren Haotian Sun Antoine Moulin Arthur Gretton Bo Dai CML 37 1 0 15 Jul 2024
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning Hao-ming Lin Wenhao Ding Jian Chen Laixi Shi Jiacheng Zhu Bo-wen Li Ding Zhao OffRL CML 59 0 0 15 Jul 2024
Graph Neural Thompson Sampling Shuang Wu Arash A. Amini 56 0 0 15 Jun 2024
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning Subhojyoti Mukherjee Josiah P. Hanna Qiaomin Xie Robert Nowak 89 2 0 07 Jun 2024
Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint Haitong Ma Zhaolin Ren Bo Dai Na Li 40 1 0 07 Apr 2024
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation Yan Dai Qiwen Cui S. S. Du 54 1 0 11 Feb 2024
Information-Theoretic State Variable Selection for Reinforcement Learning Charles Westphal Stephen Hailes Mirco Musolesi 26 3 0 21 Jan 2024
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning Hongming Zhang Tongzheng Ren Chenjun Xiao Dale Schuurmans Bo Dai 45 4 0 20 Nov 2023
Data-Guided Regulator for Adaptive Nonlinear Control Niyousha Rahimi M. Mesbahi 44 0 0 20 Nov 2023
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning Parvin Malekzadeh Ming Hou Konstantinos N. Plataniotis 51 1 0 16 Oct 2023
Stackelberg Batch Policy Learning Wenzhuo Zhou Annie Qu OffRL 35 1 0 28 Sep 2023
Online Network Source Optimization with Graph-Kernel MAB Laura Toni P. Frossard 29 1 0 07 Jul 2023
Stability of Q-Learning Through Design and Optimism Sean P. Meyn 31 10 0 05 Jul 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo Zihao Li Huazheng Wang Mengdi Wang Zhuoran Yang Xuezhou Zhang 37 5 0 21 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
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding Tongzheng Ren Zhaolin Ren Haitong Ma Na Li Bo Dai 30 10 0 08 Apr 2023
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation Thanh Nguyen-Tang R. Arora OffRL 48 5 0 24 Feb 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 31 12 0 14 Feb 2023
Online Reinforcement Learning with Uncertain Episode Lengths Debmalya Mandal Goran Radanović Jiarui Gan Adish Singla R. Majumdar OffRL 36 5 0 07 Feb 2023
Sample Complexity of Kernel-Based Q-Learning Sing-Yuan Yeh Fu-Chieh Chang Chang-Wei Yueh Pei-Yuan Wu A. Bernacchia Sattar Vakili OffRL 30 4 0 01 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 34 20 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
Refined Regret for Adversarial MDPs with Linear Function Approximation Yan Dai Haipeng Luo Chen-Yu Wei Julian Zimmert 31 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
Multi-Agent Congestion Cost Minimization With Linear Function Approximations Prashant Trivedi N. Hemachandra 37 0 0 26 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
Causal Deep Reinforcement Learning Using Observational Data Wenxuan Zhu Chao Yu Qiaosheng Zhang CML OffRL 26 5 0 28 Nov 2022
Linear Reinforcement Learning with Ball Structure Action Space Zeyu Jia Randy Jia Dhruv Madeka Dean Phillips Foster 31 1 0 14 Nov 2022
Dynamic Regret of Online Markov Decision Processes Peng Zhao Longfei Li Zhi-Hua Zhou OffRL 44 17 0 26 Aug 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
Making Linear MDPs Practical via Contrastive Representation Learning Tianjun Zhang Tongzheng Ren Mengjiao Yang Joseph E. Gonzalez Dale Schuurmans Bo Dai 25 44 0 14 Jul 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 35 38 0 12 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
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 51 32 0 24 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 50 22 0 15 Jun 2022
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization Hui Yuan Chengzhuo Ni Huazheng Wang Xuezhou Zhang Le Cong Csaba Szepesvári Mengdi Wang 28 2 0 05 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 40 5 0 01 Jun 2022
Byzantine-Robust Online and Offline Distributed Reinforcement Learning Yiding Chen Xuezhou Zhang Kaipeng Zhang Mengdi Wang Xiaojin Zhu OffRL 26 16 0 01 Jun 2022
Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal Yuda Song Wen Sun Kaiwen Wang Mengdi Wang Xuezhou Zhang OffRL 25 33 0 29 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
A Complete Characterization of Linear Estimators for Offline Policy Evaluation Juan C. Perdomo A. Krishnamurthy Peter L. Bartlett Sham Kakade OffRL 27 3 0 08 Mar 2022
Target Network and Truncation Overcome The Deadly Triad in $Q$ -Learning Zaiwei Chen John-Paul Clarke S. T. Maguluri 28 19 0 05 Mar 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching Gen Li Junbo Li Anmol Kabra Nathan Srebro Zhaoran Wang Zhuoran Yang 34 4 0 28 Dec 2021
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? Han Zhong Zhuoran Yang Zhaoran Wang Michael I. Jordan 34 30 0 27 Dec 2021
Recent Advances in Reinforcement Learning in Finance B. Hambly Renyuan Xu Huining Yang OffRL 29 168 0 08 Dec 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang Sunil R. Gupta A. Nguyen Svetha Venkatesh OffRL 34 29 0 27 Nov 2021
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren Tianjun Zhang Csaba Szepesvári Bo Dai 27 19 0 22 Nov 2021