Improved Algorithms for Misspecified Linear Markov Decision Processes

Improved Algorithms for Misspecified Linear Markov Decision Processes

12 September 2021

Advait Parulekar

Sanjay Shakkottai

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

11 / 11 papers shown

Title
Near-optimal Representation Learning for Linear Bandits and Linear RL Jiachen Hu Xiaoyu Chen Chi Jin Lihong Li Liwei Wang OffRL 143 53 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 58 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 365 207 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
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration Andrea Zanette David Brandfonbrener Emma Brunskill Matteo Pirotta A. Lazaric 62 130 0 01 Nov 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 81 27 0 06 Sep 2016