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Model-free Representation Learning and Exploration in Low-rank MDPs

14 February 2021

Papers citing "Model-free Representation Learning and Exploration in Low-rank MDPs"

31 / 31 papers shown

Title
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 253 10 0 19 Sep 2024
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 249 167 0 06 Jan 2021
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL Aldo Pacchiano Christoph Dann Claudio Gentile Peter L. Bartlett 72 49 0 24 Dec 2020
Online Model Selection for Reinforcement Learning with Function Approximation Jonathan Lee Aldo Pacchiano Vidya Muthukumar Weihao Kong Emma Brunskill OffRL 50 37 0 19 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 70 18 0 09 Nov 2020
Online Sparse Reinforcement Learning Botao Hao Tor Lattimore Csaba Szepesvári Mengdi Wang OffRL 83 29 0 08 Nov 2020
The Elliptical Potential Lemma Revisited Alexandra Carpentier Claire Vernade Yasin Abbasi-Yadkori 167 21 0 20 Oct 2020
Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective Dylan J. Foster Alexander Rakhlin D. Simchi-Levi Yunzong Xu 149 77 0 07 Oct 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 71 64 0 18 Aug 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning Alekh Agarwal Mikael Henaff Sham Kakade Wen Sun OffRL 67 110 0 16 Jul 2020
On Reward-Free Reinforcement Learning with Linear Function Approximation Ruosong Wang S. Du Lin F. Yang Ruslan Salakhutdinov OffRL 68 107 0 19 Jun 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 165 226 0 18 Jun 2020
Learning Invariant Representations for Reinforcement Learning without Reconstruction Amy Zhang R. McAllister Roberto Calandra Y. Gal Sergey Levine OOD SSL 106 476 0 18 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 91 305 0 01 Jun 2020
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension Ruosong Wang Ruslan Salakhutdinov Lin F. Yang 62 55 0 21 May 2020
Planning to Explore via Self-Supervised World Models Ramanan Sekar Oleh Rybkin Kostas Daniilidis Pieter Abbeel Danijar Hafner Deepak Pathak SSL 72 407 0 12 May 2020
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 169 196 0 07 Feb 2020
Learning with Good Feature Representations in Bandits and in RL with a Generative Model Tor Lattimore Csaba Szepesvári Gellert Weisz OffRL 163 171 0 18 Nov 2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 79 151 0 13 Nov 2019
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles Aditya Modi Nan Jiang Ambuj Tewari Satinder Singh 68 131 0 23 Oct 2019
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? S. Du Sham Kakade Ruosong Wang Lin F. Yang 181 193 0 07 Oct 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning Carles Gelada Saurabh Kumar Jacob Buckman Ofir Nachum Marc G. Bellemare BDL 81 287 0 06 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 62 286 0 24 May 2019
Information-Theoretic Considerations in Batch Reinforcement Learning Jinglin Chen Nan Jiang OOD OffRL 161 377 0 01 May 2019
A Geometric Perspective on Optimal Representations for Reinforcement Learning Marc G. Bellemare Will Dabney Robert Dadashi Adrien Ali Taïga Pablo Samuel Castro Nicolas Le Roux Dale Schuurmans Tor Lattimore Clare Lyle 57 90 0 31 Jan 2019
Provably efficient RL with Rich Observations via Latent State Decoding S. Du A. Krishnamurthy Nan Jiang Alekh Agarwal Miroslav Dudík John Langford OffRL 66 230 0 25 Jan 2019
Learning Latent Dynamics for Planning from Pixels Danijar Hafner Timothy Lillicrap Ian S. Fischer Ruben Villegas David R Ha Honglak Lee James Davidson BDL 88 1,437 0 12 Nov 2018
On Oracle-Efficient PAC RL with Rich Observations Christoph Dann Nan Jiang A. Krishnamurthy Alekh Agarwal John Langford Robert Schapire 49 98 0 01 Mar 2018
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 111 2,439 0 15 May 2017
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable Nan Jiang A. Krishnamurthy Alekh Agarwal John Langford Robert Schapire 147 420 0 29 Oct 2016
Model-based Reinforcement Learning and the Eluder Dimension Ian Osband Benjamin Van Roy 92 190 0 07 Jun 2014