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07/25/2023
Source Condition Double Robust Inference on Functionals of Inverse Problems
We consider estimation of parameters defined as linear functionals of so...
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06/13/2023
Learning under Selective Labels with Data from Heterogeneous Decision-makers: An Instrumental Variable Approach
We study the problem of learning with selectively labeled data, which ar...
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04/04/2023
Online Joint Assortment-Inventory Optimization under MNL Choices
We study an online joint assortment-inventory optimization problem, in w...
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02/10/2023
Minimax Instrumental Variable Regression and L_2 Convergence Guarantees without Identification or Closedness
In this paper, we study nonparametric estimation of instrumental variabl...
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08/17/2022
Debiased Inference on Identified Linear Functionals of Underidentified Nuisances via Penalized Minimax Estimation
We study generic inference on identified linear functionals of nonunique...
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02/19/2022
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning
Off-policy evaluation and learning (OPE/L) use offline observational dat...
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02/15/2022
Long-term Causal Inference Under Persistent Confounding via Data Combination
We study the identification and estimation of long-term treatment effect...
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08/09/2021
Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models
We develop a new approach for identifying and estimating average causal ...
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03/25/2021
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach
We study the estimation of causal parameters when not all confounders ar...
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11/05/2020
Fast Rates for Contextual Linear Optimization
Incorporating side observations of predictive features can help reduce u...
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08/17/2020
Stochastic Optimization Forests
We study conditional stochastic optimization problems, where we leverage...
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03/27/2020
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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12/30/2019
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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09/05/2019
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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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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11/27/2018
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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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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06/03/2018
