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Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation


Mar 24, 2021
Andrea Zanette, Ching-An Cheng, Alekh Agarwal

* Initial submission 

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Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL


Dec 14, 2020
Andrea Zanette

* Initial submission 

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Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration


Aug 18, 2020
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill


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Learning Near Optimal Policies with Low Inherent Bellman Error


Mar 05, 2020
Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill

* Minor fix 

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Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs


Nov 03, 2019
Andrea Zanette, Emma Brunskill

* International Conference on Machine Learning, 2018 

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Frequentist Regret Bounds for Randomized Least-Squares Value Iteration


Nov 01, 2019
Andrea Zanette, David Brandfonbrener, Matteo Pirotta, Alessandro Lazaric


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Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds


Jan 01, 2019
Andrea Zanette, Emma Brunskill


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Robust Super-Level Set Estimation using Gaussian Processes


Nov 25, 2018
Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer

* Accepted to ECML 2018 

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