publications by categories in reversed chronological order. generated by jekyll-scholar.


  1. A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret
    Connor Lawless, and Angela Zhou
  2. Empirical Gateaux Derivatives for Causal Inference
    Michael Jordan, Yixin Wang, and Angela Zhou
    conference version at Neurips; journal version in preparation 2022
  3. Stateful Offline Contextual Policy Evaluation and Learning
    Angela Zhou, and Nathan Kallus
    Proceedings of The 25nd International Conference on Artificial Intelligence and Statistics 2022
  4. Off-Policy Evaluation with Policy-Dependent Optimization Response
    Wenshuo Guo, Michael Jordan, and Angela Zhou
    Neurips 2022


  1. Fairness, Welfare, and Equity in Personalized Pricing
    Nathan Kallus, and Angela Zhou
    ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2021
  2. It’s COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks
    Michelle Bao, Angela Zhou, Samantha Zottola, and 5 more authors
    Advances in Neural Information Processing Systems, Datasets and Benchmarks 2021 2021
  3. An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls
    Angela Zhou, Andrew Koo, Nathan Kallus, and 4 more authors
    arxiv/SSRN preprint 2021


  1. Minimax-Optimal Policy Learning under Unobserved Confounding
    Nathan Kallus, and Angela Zhou
    Management Science (Forthcoming), supersedes Neurips 2018 version 2020
  2. Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning
    Nathan Kallus, and Angela Zhou
    Neurips 2020


  1. The fairness of risk scores beyond classification: Bipartite ranking and the xauc metric
    Nathan Kallus, and Angela Zhou
    Neurips 2019
  2. Assessing algorithmic fairness with unobserved protected class using data combination
    Nathan Kallus, Xiaojie Mao, and Angela Zhou
    Management Science (Forthcoming). A preliminary version appeared at FaCCT 2020 2019
  3. Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds
    Nathan Kallus, and Angela Zhou
    Neurips 2019
  4. Interval estimation of individual-level causal effects under unobserved confounding
    Nathan Kallus, Xiaojie Mao, and Angela Zhou
    AISTATS 2019


  1. Confounding-robust policy improvement
    Nathan Kallus, and Angela Zhou
    Neurips 2018
  2. Policy Evaluation and Optimization with Continuous Treatments
    Nathan Kallus, and Angela Zhou
    AISTATS 2018
  3. Residual Unfairness in Fair Machine Learning from Prejudiced Data
    Nathan Kallus, and Angela Zhou
    ICML 2018