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

International Conference on Machine Learning (ICML), 2019

24 May 2019

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

50 / 226 papers shown

Title
Provable Representation Learning for Imitation with Contrastive Fourier FeaturesNeural Information Processing Systems (NeurIPS), 2021 Ofir Nachum Mengjiao Yang SSL OffRL 245 39 0 26 May 2021
Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing Anshumali Shrivastava Zhao Song Zhaozhuo Xu 140 22 0 18 May 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited RevisitingNeural Information Processing Systems (NeurIPS), 2021 Gen Li Yuxin Chen Yuejie Chi Yuantao Gu Yuting Wei OffRL 260 30 0 17 May 2021
Regret Bounds for Stochastic Shortest Path Problems with Linear Function ApproximationInternational Conference on Machine Learning (ICML), 2021 Daniel Vial Advait Parulekar Sanjay Shakkottai R. Srikant 279 17 0 04 May 2021
An $L^2$ Analysis of Reinforcement Learning in High Dimensions with Kernel and Neural Network ApproximationCSIAM Transactions on Applied Mathematics (CSIAM Trans. Appl. Math.), 2021 Jihao Long Jiequn Han null Weinan E OffRL 171 15 0 15 Apr 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function ApproximationAnnual Conference Computational Learning Theory (COLT), 2021 Andrea Zanette Ching-An Cheng Alekh Agarwal 300 56 0 24 Mar 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality GapNeural Information Processing Systems (NeurIPS), 2021 Yuanhao Wang Ruosong Wang Sham Kakade OffRL 392 47 0 23 Mar 2021
Provably Correct Optimization and Exploration with Non-linear PoliciesInternational Conference on Machine Learning (ICML), 2021 Fei Feng W. Yin Alekh Agarwal Lin F. Yang 230 13 0 22 Mar 2021
Dynamic Pricing and Learning under the Bass ModelACM Conference on Economics and Computation (EC), 2021 Shipra Agrawal Steven Yin A. Zeevi 195 12 0 09 Mar 2021
Provably Efficient Cooperative Multi-Agent Reinforcement Learning with Function Approximation Abhimanyu Dubey Alex Pentland 171 27 0 08 Mar 2021
MobILE: Model-Based Imitation Learning From Observation AloneNeural Information Processing Systems (NeurIPS), 2021 Rahul Kidambi Jonathan D. Chang Wen Sun 201 42 0 22 Feb 2021
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Jiafan He Dongruo Zhou Quanquan Gu 253 26 0 17 Feb 2021
Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov GamesInternational Conference on Algorithmic Learning Theory (ALT), 2021 Zixiang Chen Dongruo Zhou Quanquan Gu 146 28 0 15 Feb 2021
Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function ApproximationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Yue Wu Dongruo Zhou Quanquan Gu 149 22 0 15 Feb 2021
Model-free Representation Learning and Exploration in Low-rank MDPsJournal of machine learning research (JMLR), 2021 Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 303 85 0 14 Feb 2021
Robust Policy Gradient against Strong Data CorruptionInternational Conference on Machine Learning (ICML), 2021 Xuezhou Zhang Yiding Chen Xiaojin Zhu Wen Sun AAML 282 42 0 11 Feb 2021
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual CurvatureNeural Information Processing Systems (NeurIPS), 2021 Kefan Dong Jiaqi Yang Tengyu Ma 483 37 0 08 Feb 2021
Near-optimal Representation Learning for Linear Bandits and Linear RLInternational Conference on Machine Learning (ICML), 2021 Jiachen Hu Xiaoyu Chen Chi Jin Lihong Li Liwei Wang OffRL 229 57 0 08 Feb 2021
Tactical Optimism and Pessimism for Deep Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021 Theodore H. Moskovitz Jack Parker-Holder Aldo Pacchiano Michael Arbel Sai Li 291 69 0 07 Feb 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDPNeural Information Processing Systems (NeurIPS), 2021 Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 302 46 0 29 Jan 2021
Breaking the Deadly Triad with a Target NetworkInternational Conference on Machine Learning (ICML), 2021 Shangtong Zhang Hengshuai Yao Shimon Whiteson AAML 652 55 0 21 Jan 2021
A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Cost Minbo Gao Tianle Xie S. Du Lin F. Yang 171 51 0 02 Jan 2021
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision ProcessesAnnual Conference Computational Learning Theory (COLT), 2020 Dongruo Zhou Quanquan Gu Csaba Szepesvári 258 225 0 15 Dec 2020
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RLInternational Conference on Machine Learning (ICML), 2020 Andrea Zanette OffRL 659 74 0 14 Dec 2020
Regret Bounds for Adaptive Nonlinear ControlConference on Learning for Dynamics & Control (L4DC), 2020 Nicholas M. Boffi Stephen Tu Jean-Jacques E. Slotine 238 50 0 26 Nov 2020
Logarithmic Regret for Reinforcement Learning with Linear Function ApproximationInternational Conference on Machine Learning (ICML), 2020 Jiafan He Dongruo Zhou Quanquan Gu 196 106 0 23 Nov 2020
Model-based Reinforcement Learning for Continuous Control with Posterior SamplingInternational Conference on Machine Learning (ICML), 2020 Ying Fan Yifei Ming 291 21 0 20 Nov 2020
Online Model Selection for Reinforcement Learning with Function ApproximationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Jonathan Lee Aldo Pacchiano Vidya Muthukumar Weihao Kong Emma Brunskill OffRL 205 37 0 19 Nov 2020
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement LearningAsian Conference on Machine Learning (ACML), 2020 Sayak Ray Chowdhury Rafael Oliveira OffRL 272 5 0 16 Nov 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Sai Li 180 18 0 09 Nov 2020
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient Botao Hao Yaqi Duan Tor Lattimore Csaba Szepesvári Mengdi Wang OffRL 289 29 0 08 Nov 2020
Online Sparse Reinforcement Learning Botao Hao Tor Lattimore Csaba Szepesvári Mengdi Wang OffRL 591 30 0 08 Nov 2020
Episodic Linear Quadratic Regulators with Low-rank Transitions Tianyu Wang Lin F. Yang 154 3 0 03 Nov 2020
Efficient Learning in Non-Stationary Linear Markov Decision Processes Ahmed Touati Pascal Vincent 235 30 0 24 Oct 2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 294 22 0 23 Oct 2020
Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning? Qiwen Cui Lin F. Yang OffRL 161 14 0 12 Oct 2020
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 280 7 0 05 Oct 2020
Neural Thompson SamplingInternational Conference on Learning Representations (ICLR), 2020 Weitong Zhang Dongruo Zhou Lihong Li Quanquan Gu 254 139 0 02 Oct 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 179 65 0 18 Aug 2020
Learning Infinite-horizon Average-reward MDPs with Linear Function ApproximationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Chen-Yu Wei Mehdi Jafarnia-Jahromi Haipeng Luo Rahul Jain 270 51 0 23 Jul 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient LearningNeural Information Processing Systems (NeurIPS), 2020 Alekh Agarwal Mikael Henaff Sham Kakade Wen Sun OffRL 230 119 0 16 Jul 2020
A Unifying View of Optimism in Episodic Reinforcement Learning Gergely Neu Ciara Pike-Burke 151 74 0 03 Jul 2020
Online learning in MDPs with linear function approximation and bandit feedback Gergely Neu Julia Olkhovskaya 229 36 0 03 Jul 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature MappingInternational Conference on Machine Learning (ICML), 2020 Dongruo Zhou Jiafan He Quanquan Gu 317 141 0 23 Jun 2020
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data Lingxiao Wang Zhuoran Yang Zhaoran Wang OffRL 160 55 0 22 Jun 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 418 246 0 18 Jun 2020
A maximum-entropy approach to off-policy evaluation in average-reward MDPs N. Lazić Dong Yin Mehrdad Farajtabar Nir Levine Dilan Görür Chris Harris Dale Schuurmans OffRL 179 12 0 17 Jun 2020
Zeroth-order Deterministic Policy Gradient Harshat Kumar Dionysios S. Kalogerias George J. Pappas Alejandro Ribeiro OffRL 147 14 0 12 Jun 2020
Sample Efficient Reinforcement Learning via Low-Rank Matrix EstimationNeural Information Processing Systems (NeurIPS), 2020 Devavrat Shah Dogyoon Song Zhi Xu Yuzhe Yang 279 34 0 11 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted RegressionConference on Learning for Dynamics & Control (L4DC), 2020 Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 278 313 0 01 Jun 2020