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09/12/2023
Optimal and Fair Encouragement Policy Evaluation and Learning
In consequential domains, it is often impossible to compel individuals t...
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02/01/2023
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders
Offline reinforcement learning is important in domains such as medicine,...
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11/09/2022
A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret
In this short technical note we propose a baseline for decision-aware le...
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02/25/2022
Off-Policy Evaluation with Policy-Dependent Optimization Response
The intersection of causal inference and machine learning for decision-m...
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11/16/2021
An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls
We conduct an empirical evaluation of the impact of New York's bail refo...
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10/19/2021
Stateful Offline Contextual Policy Evaluation and Learning
We study off-policy evaluation and learning from sequential data in a st...
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06/10/2021
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks
Risk assessment instrument (RAI) datasets, particularly ProPublica's COM...
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12/21/2020
Fairness, Welfare, and Equity in Personalized Pricing
We study the interplay of fairness, welfare, and equity considerations i...
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02/11/2020
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning
Off-policy evaluation of sequential decision policies from observational...
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06/04/2019
Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds
Personalized interventions in social services, education, and healthcare...
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06/01/2019
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
The increasing impact of algorithmic decisions on people's lives compels...
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02/15/2019
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric
Where machine-learned predictive risk scores inform high-stakes decision...
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10/05/2018
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding
We study the problem of learning conditional average treatment effects (...
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06/07/2018
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Recent work in fairness in machine learning has proposed adjusting for f...
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05/22/2018
Confounding-Robust Policy Improvement
We study the problem of learning personalized decision policies from obs...
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02/16/2018
Policy Evaluation and Optimization with Continuous Treatments
We study the problem of policy evaluation and learning from batched cont...
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01/30/2017
