Learning with Good Feature Representations in Bandits and in RL with a Generative Model

18 November 2019

Papers citing "Learning with Good Feature Representations in Bandits and in RL with a Generative Model"

50 / 57 papers shown

Title
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion Akhil Jalan Yassir Jedra Arya Mazumdar Soumendu Sundar Mukherjee Purnamrita Sarkar 192 0 0 28 Feb 2025
Linear Bandits with Partially Observable Features Wonyoung Hedge Kim Sungwoo Park G. Iyengar A. Zeevi Min Hwan Oh 65 0 0 10 Feb 2025
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals Ziyi Liu Idan Attias Daniel M. Roy CML 31 0 0 01 Jul 2024
Policy Mirror Descent with Lookahead Kimon Protopapas Anas Barakat 29 1 0 21 Mar 2024
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 32 5 0 09 Oct 2023
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces Shyam Sundhar Ramesh Pier Giuseppe Sessa Yifan Hu Andreas Krause Ilija Bogunovic OOD 42 10 0 05 Sep 2023
The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation P. Amortila Nan Jiang Csaba Szepesvári OffRL 29 3 0 25 Jul 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 28 20 0 29 May 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice Toshinori Kitamura Tadashi Kozuno Yunhao Tang Nino Vieillard Michal Valko ... Olivier Pietquin M. Geist Csaba Szepesvári Wataru Kumagai Yutaka Matsuo OffRL 30 2 0 22 May 2023
Does Sparsity Help in Learning Misspecified Linear Bandits? Jialin Dong Lin F. Yang 25 1 0 29 Mar 2023
Reinforcement Learning with Function Approximation: From Linear to Nonlinear Jihao Long Jiequn Han 27 5 0 20 Feb 2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Volodymyr Tkachuk Seyed Alireza Bakhtiari Johannes Kirschner Matej Jusup Ilija Bogunovic Csaba Szepesvári 32 4 0 08 Feb 2023
(Private) Kernelized Bandits with Distributed Biased Feedback Fengjiao Li Xingyu Zhou Bo Ji 33 5 0 28 Jan 2023
Near-optimal Policy Identification in Active Reinforcement Learning Xiang Li Viraj Mehta Johannes Kirschner I. Char Willie Neiswanger J. Schneider Andreas Krause Ilija Bogunovic OffRL 43 6 0 19 Dec 2022
Linear Reinforcement Learning with Ball Structure Action Space Zeyu Jia Randy Jia Dhruv Madeka Dean Phillips Foster 25 1 0 14 Nov 2022
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms Osama A. Hanna Lin F. Yang Christina Fragouli 27 11 0 08 Nov 2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees Andrea Tirinzoni Matteo Papini Ahmed Touati A. Lazaric Matteo Pirotta 28 4 0 24 Oct 2022
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization Gergely Neu Nneka Okolo 34 6 0 21 Oct 2022
Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 50 3 0 05 Oct 2022
Best Policy Identification in Linear MDPs Jerome Taupin Yassir Jedra Alexandre Proutière 44 3 0 11 Aug 2022
Differentially Private Linear Bandits with Partial Distributed Feedback Fengjiao Li Xingyu Zhou Bo Ji FedML 34 13 0 12 Jul 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 66 46 0 13 May 2022
Efficient Active Learning with Abstention Yinglun Zhu Robert D. Nowak 49 11 0 31 Mar 2022
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles Aldo G. Carranza Sanath Kumar Krishnamurthy Susan Athey 19 1 0 30 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
Exponential Family Model-Based Reinforcement Learning via Score Matching Gen Li Junbo Li Anmol Kabra Nathan Srebro Zhaoran Wang Zhuoran Yang 32 4 0 28 Dec 2021
Recent Advances in Reinforcement Learning in Finance B. Hambly Renyuan Xu Huining Yang OffRL 29 167 0 08 Dec 2021
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation Dylan J. Foster A. Krishnamurthy D. Simchi-Levi Yunzong Xu OffRL 21 62 0 21 Nov 2021
Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning Vincent Liu James Wright Martha White OffRL 31 1 0 15 Nov 2021
Misspecified Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause 57 42 0 09 Nov 2021
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification Clémence Réda Andrea Tirinzoni Rémy Degenne 31 9 0 02 Nov 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
When Are Linear Stochastic Bandits Attackable? Huazheng Wang Haifeng Xu Hongning Wang AAML 37 10 0 18 Oct 2021
Bad-Policy Density: A Measure of Reinforcement Learning Hardness David Abel Cameron Allen Dilip Arumugam D Ellis Hershkowitz Michael L. Littman Lawson L. S. Wong 26 2 0 07 Oct 2021
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits Yinglun Zhu Julian Katz-Samuels Robert D. Nowak 38 6 0 10 Sep 2021
Efficient Local Planning with Linear Function Approximation Dong Yin Botao Hao Yasin Abbasi-Yadkori N. Lazić Csaba Szepesvári 32 19 0 12 Aug 2021
Bayesian decision-making under misspecified priors with applications to meta-learning Max Simchowitz Christopher Tosh A. Krishnamurthy Daniel J. Hsu Thodoris Lykouris Miroslav Dudík Robert Schapire 40 49 0 03 Jul 2021
On component interactions in two-stage recommender systems Jiri Hron K. Krauth Michael I. Jordan Niki Kilbertus CML LRM 40 31 0 28 Jun 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? Kate Rakelly Abhishek Gupta Carlos Florensa Sergey Levine SSL 26 38 0 14 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
Leveraging Good Representations in Linear Contextual Bandits Matteo Papini Andrea Tirinzoni Marcello Restelli A. Lazaric Matteo Pirotta 30 26 0 08 Apr 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap Yuanhao Wang Ruosong Wang Sham Kakade OffRL 39 43 0 23 Mar 2021
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games Yu Bai Chi Jin Haiquan Wang Caiming Xiong 44 67 0 23 Feb 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 166 0 06 Jan 2021
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
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
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 20 64 0 18 Aug 2020
Efficient Planning in Large MDPs with Weak Linear Function Approximation R. Shariff Csaba Szepesvári 39 22 0 13 Jul 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 30 133 0 23 Jun 2020