Model Selection for Generic Reinforcement Learning

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Model Selection for Generic Reinforcement Learning

13 July 2021

Sayak Ray Chowdhury

Kannan Ramchandran

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Papers citing "Model Selection for Generic Reinforcement Learning"

15 / 15 papers shown

Title
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL Aldo Pacchiano Christoph Dann Claudio Gentile Peter L. Bartlett 87 49 0 24 Dec 2020
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 88 209 0 15 Dec 2020
Information Theoretic Regret Bounds for Online Nonlinear Control Sham Kakade A. Krishnamurthy Kendall Lowrey Motoya Ohnishi Wen Sun 81 119 0 22 Jun 2020
Corralling Stochastic Bandit Algorithms R. Arora T. V. Marinov M. Mohri 97 35 0 16 Jun 2020
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits Avishek Ghosh Abishek Sankararaman Kannan Ramchandran 64 34 0 04 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 101 305 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 77 55 0 21 May 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 186 137 0 09 Dec 2019
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration Andrea Zanette David Brandfonbrener Emma Brunskill Matteo Pirotta A. Lazaric 138 132 0 01 Nov 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 111 560 0 11 Jul 2019
Model selection for contextual bandits Dylan J. Foster A. Krishnamurthy Haipeng Luo OffRL 206 90 0 03 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 93 288 0 24 May 2019
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization Xinyang Yi Constantine Caramanis Sujay Sanghavi 82 60 0 19 Aug 2016
Statistical guarantees for the EM algorithm: From population to sample-based analysis Sivaraman Balakrishnan Martin J. Wainwright Bin Yu 323 482 0 09 Aug 2014
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 137 12,272 0 19 Dec 2013