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A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes


Jul 30, 2022
Kelly W. Zhang, Omer Gottesman, Finale Doshi-Velez

* Challenges of Real-World Reinforcement Learning 2020 (NeurIPS Workshop) 

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Deep Q-Network with Proximal Iteration


Dec 10, 2021
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola

* Work in Progress 

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Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation


Nov 28, 2021
Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill


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Coarse-Grained Smoothness for RL in Metric Spaces


Oct 23, 2021
Omer Gottesman, Kavosh Asadi, Cameron Allen, Sam Lobel, George Konidaris, Michael Littman


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State Relevance for Off-Policy Evaluation


Sep 13, 2021
Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez

* Proceedings of the 38th International Conference on Machine Learning, PMLR 139:9537-9546, 2021 
* ICML 2021 

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Learning Markov State Abstractions for Deep Reinforcement Learning


Jun 08, 2021
Cameron Allen, Neev Parikh, Omer Gottesman, George Konidaris

* Code available at https://github.com/camall3n/markov-state-abstractions 

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Learning to search efficiently for causally near-optimal treatments


Jul 02, 2020
Samuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson


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Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions


Feb 14, 2020
Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez

* Change: Correction of typo in meta-data author names 

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A general method for regularizing tensor decomposition methods via pseudo-data


May 24, 2019
Omer Gottesman, Weiwei Pan, Finale Doshi-Velez


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