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Machine learning and causality: Building efficient, and reliable models for decision-making.

. Massachusetts Institute of Technology, USA, (2021)

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Machine learning and causality: Building efficient, and reliable models for decision-making.. Massachusetts Institute of Technology, USA, (2021)Causally motivated multi-shortcut identification and removal., and . NeurIPS, (2022)Exploiting structured data for learning contagious diseases under incomplete testing., , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 7348-7357. PMLR, (2021)Uncovering the Varied Impact of Behavioral Change Messages on Population Groups., , , , and . MLHC, volume 219 of Proceedings of Machine Learning Research, page 906-922. PMLR, (2023)Partial identification of kernel based two sample tests with mismeasured data., and . CoRR, (2023)Fairness and robustness in anti-causal prediction., and . CoRR, (2022)Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare., , , , and . NeurIPS, (2022)Causally Motivated Multiple Shortcut Removal Using High Dimensional Auxiliary Labels., and . AMIA, AMIA, (2022)Learning to Rank for Optimal Treatment Allocation Under Resource Constraints., , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3727-3735. PMLR, (2024)A Distillation Approach to Data Efficient Individual Treatment Effect Estimation., , and . AAAI, page 4544-4551. AAAI Press, (2019)