Improved Algorithms for Misspecified Linear Markov Decision Processes

12 September 2021

Papers citing "Improved Algorithms for Misspecified Linear Markov Decision Processes"

10 / 10 papers shown

Title
Near-optimal Representation Learning for Linear Bandits and Linear RL Jiachen Hu Xiaoyu Chen Chi Jin Lihong Li Liwei Wang OffRL 137 51 0 08 Feb 2021
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL Aldo Pacchiano Christoph Dann Claudio Gentile Peter L. Bartlett 54 49 0 24 Dec 2020
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 66 207 0 15 Dec 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 65 64 0 18 Aug 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 55 135 0 23 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 83 304 0 01 Jun 2020
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles Dylan J. Foster Alexander Rakhlin 344 207 0 12 Feb 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 168 136 0 09 Dec 2019
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 89 306 0 22 Mar 2017
Low-rank Bandits with Latent Mixtures Aditya Gopalan Odalric-Ambrym Maillard Mohammadi Zaki 75 27 0 06 Sep 2016