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Michael Oberst

Massachusetts Institute of Technology

Auditing Fairness under Unobserved Confounding

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Mar 18, 2024
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Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium

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Mar 03, 2024
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Benchmarking Observational Studies with Experimental Data under Right-Censoring

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Feb 23, 2024
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Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions

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Jan 30, 2023
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Falsification before Extrapolation in Causal Effect Estimation

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Sep 29, 2022
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Evaluating Robustness to Dataset Shift via Parametric Robustness Sets

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May 31, 2022
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Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance

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Oct 27, 2021
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Regularizing towards Causal Invariance: Linear Models with Proxies

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Mar 03, 2021
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Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies

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Oct 08, 2020
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Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes

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Jun 01, 2020
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