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Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies


Nov 05, 2021
Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel Jiang, Eytan Bakshy

* A short version was presented at MIT CODE 2021 

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Efficient Balanced Treatment Assignments for Experimentation


Oct 21, 2020
David Arbour, Drew Dimmery, Anup Rao


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Real-world Video Adaptation with Reinforcement Learning


Aug 28, 2020
Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy

* Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019 

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Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints


Nov 02, 2019
Samuel Daulton, Shaun Singh, Vashist Avadhanula, Drew Dimmery, Eytan Bakshy

* To appear at NeurIPS 2019, Workshop on Safety and Robustness in Decision Making. 11 pages (including references and appendix) 

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Balanced Off-Policy Evaluation in General Action Spaces


Jun 13, 2019
Arjun Sondhi, David Arbour, Drew Dimmery


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Balanced Off-Policy Evaluation General Action Spaces


Jun 09, 2019
Arjun Sondhi, David Arbour, Drew Dimmery


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