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Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning
Off-policy evaluation of sequential decision policies from observational...
02/11/2020 ∙ by Nathan Kallus, et al. ∙
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Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds
Personalized interventions in social services, education, and healthcare...
06/04/2019 ∙ by Nathan Kallus, et al. ∙
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Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
The increasing impact of algorithmic decisions on people's lives compels...
06/01/2019 ∙ by Nathan Kallus, et al. ∙
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The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric
Where machine-learned predictive risk scores inform high-stakes decision...
02/15/2019 ∙ by Nathan Kallus, et al. ∙
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Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding
We study the problem of learning conditional average treatment effects (...
10/05/2018 ∙ by Nathan Kallus, et al. ∙
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Residual Unfairness in Fair Machine Learning from Prejudiced Data
Recent work in fairness in machine learning has proposed adjusting for f...
06/07/2018 ∙ by Nathan Kallus, et al. ∙
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Confounding-Robust Policy Improvement
We study the problem of learning personalized decision policies from obs...
05/22/2018 ∙ by Nathan Kallus, et al. ∙
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Policy Evaluation and Optimization with Continuous Treatments
We study the problem of policy evaluation and learning from batched cont...
02/16/2018 ∙ by Nathan Kallus, et al. ∙
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Dynamic Task Allocation for Crowdsourcing Settings
We consider the problem of optimal budget allocation for crowdsourcing p...
01/30/2017 ∙ by Angela Zhou, et al. ∙
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