Provably Efficient Reinforcement Learning with Linear Function
Approximation

Provably Efficient Reinforcement Learning with Linear Function Approximation

11 July 2019

Michael I. Jordan

Papers citing "Provably Efficient Reinforcement Learning with Linear Function Approximation"

11 / 161 papers shown

Title
Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate Yufeng Zhang Qi Cai Zhuoran Yang Zhaoran Wang 116 12 0 08 Mar 2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization Dongsheng Ding Xiaohan Wei Zhuoran Yang Zhaoran Wang M. Jovanović 20 159 0 01 Mar 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie Yudong Chen Zhaoran Wang Zhuoran Yang 39 124 0 17 Feb 2020
Adaptive Approximate Policy Iteration Botao Hao N. Lazić Yasin Abbasi-Yadkori Pooria Joulani Csaba Szepesvári 18 14 0 08 Feb 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 135 135 0 09 Dec 2019
Learning with Good Feature Representations in Bandits and in RL with a Generative Model Tor Lattimore Csaba Szepesvári Gellert Weisz OffRL 14 168 0 18 Nov 2019
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles Aditya Modi Nan Jiang Ambuj Tewari Satinder Singh 15 129 0 23 Oct 2019
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? S. Du Sham Kakade Ruosong Wang Lin F. Yang 27 192 0 07 Oct 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 37 186 0 05 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 13 283 0 24 May 2019
Deep Reinforcement Learning for Dialogue Generation Jiwei Li Will Monroe Alan Ritter Michel Galley Jianfeng Gao Dan Jurafsky 220 1,328 0 05 Jun 2016