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Giving Feedback on Interactive Student Programs with Meta-Exploration


Nov 16, 2022
Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn

* Advances in Neural Information Processing Systems (NeurIPS 2022). Selected as Oral 

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Oracle Inequalities for Model Selection in Offline Reinforcement Learning


Nov 03, 2022
Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill


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Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data


Oct 16, 2022
Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill

* 32 pages. To be published at NeurIPS 2022. Presented at RLDM 2022 

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Offline Policy Optimization with Eligible Actions


Jul 01, 2022
Yao Liu, Yannis Flet-Berliac, Emma Brunskill

* Accepted at the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022) 

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Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning


Dec 30, 2021
Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill

* AAAI2022 

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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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Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects


Nov 15, 2021
Steve Yadlowsky, Scott Fleming, Nigam Shah, Emma Brunskill, Stefan Wager


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Play to Grade: Testing Coding Games as Classifying Markov Decision Process


Oct 27, 2021
Allen Nie, Emma Brunskill, Chris Piech

* NeurIPS 2021, 16 pages, 7 figures 

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Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making


Sep 18, 2021
Alex Chohlas-Wood, Madison Coots, Emma Brunskill, Sharad Goel


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Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning


Aug 19, 2021
Andrea Zanette, Martin J. Wainwright, Emma Brunskill

* Initial submission; appeared as spotlight talk in ICML 2021 Workshop on Theory of RL 

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