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Future-Dependent Value-Based Off-Policy Evaluation in POMDPs


Jul 26, 2022
Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun


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Learning Bellman Complete Representations for Offline Policy Evaluation


Jul 12, 2022
Jonathan D. Chang, Kaiwen Wang, Nathan Kallus, Wen Sun

* Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2938-2971, 2022 
* Accepted for Long Talk at ICML 2022 

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Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings


Jun 24, 2022
Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun


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Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems


Jun 24, 2022
Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun


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Robust and Agnostic Learning of Conditional Distributional Treatment Effects


May 23, 2022
Nathan Kallus, Miruna Oprescu


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What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment


May 20, 2022
Nathan Kallus


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Estimating Structural Disparities for Face Models


Apr 13, 2022
Shervin Ardeshir, Cristina Segalin, Nathan Kallus

* Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022 

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Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning


Feb 19, 2022
Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou


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Long-term Causal Inference Under Persistent Confounding via Data Combination


Feb 15, 2022
Guido Imbens, Nathan Kallus, Xiaojie Mao, Yuhao Wang


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Treatment Effect Risk: Bounds and Inference


Jan 15, 2022
Nathan Kallus


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