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Fast Rates for Contextual Linear Optimization
Incorporating side observations of predictive features can help reduce u...
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Stochastic Optimization Forests
We study conditional stochastic optimization problems, where we leverage...
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On the role of surrogates in the efficient estimation of treatment effects with limited outcome data
We study the problem of estimating treatment effects when the outcome of...
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Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond
We consider the efficient estimation of a low-dimensional parameter in t...
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Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes
We study a nonparametric contextual bandit problem where the expected re...
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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...
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Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved
Assessing the fairness of a decision making system with respect to a pro...
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Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding
We study the problem of learning conditional average treatment effects (...
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Causal Inference with Noisy and Missing Covariates via Matrix Factorization
Valid causal inference in observational studies often requires controlli...
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