Angela Zhou

发表

Assessing algorithmic fairness with unobserved protected class using data combination

Xiaojie Mao, Nathan Kallus, Angela Zhou, 2019, FAT*.

It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks

Sarah L. Desmarais, Samantha A. Zottola, S. Venkatasubramanian, 2021, NeurIPS Datasets and Benchmarks.

Empirical Gateaux Derivatives for Causal Inference

M.I. Jordan, Angela Zhou, Yixin Wang, 2022, 2208.13701.

Off-Policy Evaluation with Policy-Dependent Optimization Response

M.I. Jordan, Wenshuo Guo, Angela Zhou, 2022, NeurIPS.

Empirical Gateaux Derivatives for Causal Inference

M.I. Jordan, Angela Zhou, Yixin Wang, 2022, ArXiv.

A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret

Angela Zhou, Connor Lawless, 2022, ArXiv.

Stateful Offline Contextual Policy Evaluation and Learning pdf

Nathan Kallus, Angela Zhou, Nathan Kallus, 2021, AISTATS.

Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding

Xiaojie Mao, Nathan Kallus, Angela Zhou, 2018, AISTATS.

Minimax-Optimal Policy Learning Under Unobserved Confounding

Nathan Kallus, Angela Zhou, Nathan Kallus, 2020, Manag. Sci..

Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning pdf

Nathan Kallus, Angela Zhou, Nathan Kallus, 2020, NeurIPS.

All Aboard: Can High Speed Rail Get Back on Track?

Angela Zhou, Kevin Zhou, S. Guo, 2012 .

Residual Unfairness in Fair Machine Learning from Prejudiced Data

Nathan Kallus, Angela Zhou, Nathan Kallus, 2018, ICML.

Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders

Angela Zhou, David Bruns-Smith, 2023, ArXiv.

Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds

Nathan Kallus, Angela Zhou, Nathan Kallus, 2019, ArXiv.

The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric

Nathan Kallus, Angela Zhou, Nathan Kallus, 2019, NeurIPS.

Confounding-Robust Policy Improvement

Nathan Kallus, Angela Zhou, Nathan Kallus, 2018, NeurIPS.

Data-Driven Influence Functions for Optimization-Based Causal Inference

Michael I. Jordan, M.I. Jordan, Angela Zhou, 2022, 2208.13701.

Empirical Gateaux Derivatives for Causal Inference

Michael I. Jordan, M.I. Jordan, Angela Zhou, 2022, NeurIPS.

Policy Evaluation and Optimization with Continuous Treatments

Nathan Kallus, Angela Zhou, Nathan Kallus, 2018, AISTATS.

Residual Unfairness in Fair Machine Learning from Prejudiced Data

Nathan Kallus, Angela Zhou, 2018, ICML.

Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders

Angela Zhou, David Bruns-Smith, 2023, ArXiv.

Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds

Nathan Kallus, Angela Zhou, 2019, Neural Information Processing Systems.