Angela Zhou

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 39

Top Topics

Bipartite Ranking

Interval Estimation

Reinforcement Learning

Policy Evaluation

Top Venues

Publications

Ezinne Nwankwo, Michael I. Jordan, Angela Zhou
Reduced-Rank Multi-objective Policy Learning and Optimization. CoRR (2024)
Angela Zhou
Reward-Relevance-Filtered Linear Offline Reinforcement Learning. CoRR (2024)
Angela Zhou
Orthogonalized Estimation of Difference of Q-functions. CoRR (2024)
Christoph Kern, Michael Kim, Angela Zhou
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts. CoRR (2024)
Angela Zhou
Reward-Relevance-Filtered Linear Offline Reinforcement Learning. AISTATS (2024)
Angela Zhou
Optimal and Fair Encouragement Policy Evaluation and Learning. CoRR (2023)
David Bruns-Smith, Angela Zhou
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders. CoRR (2023)
Angela Zhou
Optimal and Fair Encouragement Policy Evaluation and Learning. NeurIPS (2023)
Michael I. Jordan, Yixin Wang, Angela Zhou
Empirical Gateaux Derivatives for Causal Inference. CoRR (2022)
Nathan Kallus, Angela Zhou
Stateful Offline Contextual Policy Evaluation and Learning. AISTATS (2022)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. Manag. Sci. 68 (3) (2022)
Wenshuo Guo, Michael I. Jordan, Angela Zhou
Off-Policy Evaluation with Policy-Dependent Optimization Response. CoRR (2022)
Michael I. Jordan, Yixin Wang, Angela Zhou
Empirical Gateaux Derivatives for Causal Inference. NeurIPS (2022)
Connor Lawless, Angela Zhou
A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret. CoRR (2022)
Wenshuo Guo, Michael I. Jordan, Angela Zhou
Off-Policy Evaluation with Policy-Dependent Optimization Response. NeurIPS (2022)
Angela Zhou, Andrew Koo, Nathan Kallus, Rene Ropac, Richard Peterson, Stephen Koppel, Tiffany Bergin
An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls. CoRR (2021)
Nathan Kallus, Angela Zhou
Stateful Offline Contextual Policy Evaluation and Learning. CoRR (2021)
Nathan Kallus, Angela Zhou
Minimax-Optimal Policy Learning Under Unobserved Confounding. Manag. Sci. 67 (5) (2021)
Nathan Kallus, Angela Zhou
Fairness, Welfare, and Equity in Personalized Pricing. FAccT (2021)
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. NeurIPS Datasets and Benchmarks (2021)
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. CoRR (2021)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Assessing algorithmic fairness with unobserved protected class using data combination. FAT* (2020)
Nathan Kallus, Angela Zhou
Fairness, Welfare, and Equity in Personalized Pricing. CoRR (2020)
Nathan Kallus, Angela Zhou
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning. NeurIPS (2020)
Nathan Kallus, Angela Zhou
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning. CoRR (2020)
Nathan Kallus, Angela Zhou
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric. CoRR (2019)
Nathan Kallus, Angela Zhou
Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds. NeurIPS (2019)
Nathan Kallus, Angela Zhou
Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds. CoRR (2019)
Nathan Kallus, Angela Zhou
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric. NeurIPS (2019)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. CoRR (2019)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. AISTATS (2019)
Nathan Kallus, Angela Zhou
Policy Evaluation and Optimization with Continuous Treatments. CoRR (2018)
Nathan Kallus, Angela Zhou
Confounding-Robust Policy Improvement. NeurIPS (2018)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. CoRR (2018)
Nathan Kallus, Angela Zhou
Residual Unfairness in Fair Machine Learning from Prejudiced Data. ICML (2018)
Nathan Kallus, Angela Zhou
Confounding-Robust Policy Improvement. CoRR (2018)
Nathan Kallus, Angela Zhou
Policy Evaluation and Optimization with Continuous Treatments. AISTATS (2018)
Nathan Kallus, Angela Zhou
Residual Unfairness in Fair Machine Learning from Prejudiced Data. CoRR (2018)
Irineo Cabreros, Karan Singh, Angela Zhou
A Mixture Model and Task Allocation Scheme for Crowdsourcing. CoRR (2017)