Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Xiaojie Mao

Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach


Mar 29, 2021
Nathan Kallus, Xiaojie Mao, Masatoshi Uehara


  Access Paper or Ask Questions

Fast Rates for Contextual Linear Optimization


Nov 05, 2020
Yichun Hu, Nathan Kallus, Xiaojie Mao


  Access Paper or Ask Questions

Stochastic Optimization Forests


Sep 08, 2020
Nathan Kallus, Xiaojie Mao


  Access Paper or Ask Questions

On the role of surrogates in the efficient estimation of treatment effects with limited outcome data


Mar 27, 2020
Nathan Kallus, Xiaojie Mao


  Access Paper or Ask Questions

Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond


Dec 30, 2019
Nathan Kallus, Xiaojie Mao, Masatoshi Uehara


  Access Paper or Ask Questions

Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes


Sep 05, 2019
Yichun Hu, Nathan Kallus, Xiaojie Mao


  Access Paper or Ask Questions

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination


Jun 01, 2019
Nathan Kallus, Xiaojie Mao, Angela Zhou


  Access Paper or Ask Questions

Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved


Nov 27, 2018
Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell

* 13 pages, 11 figures, FAT*' 19: Conference on Fairness, Accountability, and Transparency (FAT*' 19), January 29-31, 2019, Atlanta, GA, USA 

  Access Paper or Ask Questions

Causal Inference with Noisy and Missing Covariates via Matrix Factorization


Jun 03, 2018
Nathan Kallus, Xiaojie Mao, Madeleine Udell

* 26 pages, 5 figures 

  Access Paper or Ask Questions