Angela Zhou - RankMe

45 papers A* 8A 4Journal 29Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Batch-Adaptive Annotations for Causal Inference with Complex-Embedded Outcomes. CoRR Ezinne Nwankwo, Lauri Goldkind, Angela Zhou
2025	J	`jnl`	Bridging Prediction and Intervention Problems in Social Systems. CoRR Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson
2025	—	`conf`	Decoding Risky Decision-Making from Nonlinear Neural Latent Dynamics. IEEECONF Angela Zhou, Logan Peters, Karen A. Moxon
2025	J	`jnl`	Fostering the Ecosystem of AI for Social Impact Requires Expanding and Strengthening Evaluation Standards. CoRR Bryan Wilder, Angela Zhou
2024	J	`jnl`	Multi-Accurate CATE is Robust to Unknown Covariate Shifts. Trans. Mach. Learn. Res. Christoph Kern, Michael P. Kim, Angela Zhou
2024	J	`jnl`	Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts. CoRR Christoph Kern, Michael P. Kim, Angela Zhou
2024	J	`jnl`	Orthogonalized Estimation of Difference of Q-functions. CoRR Angela Zhou
2024	J	`jnl`	Reduced-Rank Multi-objective Policy Learning and Optimization. CoRR Ezinne Nwankwo, Michael I. Jordan, Angela Zhou
2024	A	`conf`	Reward-Relevance-Filtered Linear Offline Reinforcement Learning. AISTATS Angela Zhou
2024	J	`jnl`	Reward-Relevance-Filtered Linear Offline Reinforcement Learning. CoRR Angela Zhou
2023	A*	`conf`	Optimal and Fair Encouragement Policy Evaluation and Learning. NeurIPS Angela Zhou
2023	J	`jnl`	Optimal and Fair Encouragement Policy Evaluation and Learning. CoRR Angela Zhou
2023	J	`jnl`	Report on the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 2022). SIGecom Exch. Elena Falcettoni, Dina Machuve, Bryan Wilder, Angela Zhou
2023	J	`jnl`	Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders. CoRR David Bruns-Smith, Angela Zhou
2022	J	`jnl`	A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret. CoRR Connor Lawless, Angela Zhou
2022	J	`jnl`	Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. Manag. Sci. Nathan Kallus, Xiaojie Mao, Angela Zhou
2022	A*	`conf`	Empirical Gateaux Derivatives for Causal Inference. NeurIPS Michael I. Jordan, Yixin Wang, Angela Zhou
2022	J	`jnl`	Empirical Gateaux Derivatives for Causal Inference. CoRR Michael I. Jordan, Yixin Wang, Angela Zhou
2022	A*	`conf`	Off-Policy Evaluation with Policy-Dependent Optimization Response. NeurIPS Wenshuo Guo, Michael I. Jordan, Angela Zhou
2022	J	`jnl`	Off-Policy Evaluation with Policy-Dependent Optimization Response. CoRR Wenshuo Guo, Michael I. Jordan, Angela Zhou
2022	A	`conf`	Stateful Offline Contextual Policy Evaluation and Learning. AISTATS Nathan Kallus, Angela Zhou
2021	J	`jnl`	An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls. CoRR Angela Zhou, Andrew Koo, Nathan Kallus, Rene Ropac, Richard Peterson, Stephen Koppel, Tiffany Bergin
2021	—	`conf`	Fairness, Welfare, and Equity in Personalized Pricing. FAccT Nathan Kallus, Angela Zhou
2021	—	`conf`	It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. NeurIPS Datasets and Benchmarks Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
2021	J	`jnl`	It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. CoRR Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
2021	J	`jnl`	Minimax-Optimal Policy Learning Under Unobserved Confounding. Manag. Sci. Nathan Kallus, Angela Zhou
2021	J	`jnl`	Stateful Offline Contextual Policy Evaluation and Learning. CoRR Nathan Kallus, Angela Zhou
2020	—	`conf`	Assessing algorithmic fairness with unobserved protected class using data combination. FAT* Nathan Kallus, Xiaojie Mao, Angela Zhou
2020	A*	`conf`	Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning. NeurIPS Nathan Kallus, Angela Zhou
2020	J	`jnl`	Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning. CoRR Nathan Kallus, Angela Zhou
2020	J	`jnl`	Fairness, Welfare, and Equity in Personalized Pricing. CoRR Nathan Kallus, Angela Zhou
2019	J	`jnl`	Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. CoRR Nathan Kallus, Xiaojie Mao, Angela Zhou
2019	A*	`conf`	Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds. NeurIPS Nathan Kallus, Angela Zhou
2019	J	`jnl`	Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds. CoRR Nathan Kallus, Angela Zhou
2019	A	`conf`	Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. AISTATS Nathan Kallus, Xiaojie Mao, Angela Zhou
2019	A*	`conf`	The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric. NeurIPS Nathan Kallus, Angela Zhou
2019	J	`jnl`	The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric. CoRR Nathan Kallus, Angela Zhou
2018	A*	`conf`	Confounding-Robust Policy Improvement. NeurIPS Nathan Kallus, Angela Zhou
2018	J	`jnl`	Confounding-Robust Policy Improvement. CoRR Nathan Kallus, Angela Zhou
2018	J	`jnl`	Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. CoRR Nathan Kallus, Xiaojie Mao, Angela Zhou
2018	A	`conf`	Policy Evaluation and Optimization with Continuous Treatments. AISTATS Nathan Kallus, Angela Zhou
2018	J	`jnl`	Policy Evaluation and Optimization with Continuous Treatments. CoRR Nathan Kallus, Angela Zhou
2018	A*	`conf`	Residual Unfairness in Fair Machine Learning from Prejudiced Data. ICML Nathan Kallus, Angela Zhou
2018	J	`jnl`	Residual Unfairness in Fair Machine Learning from Prejudiced Data. CoRR Nathan Kallus, Angela Zhou
2017	J	`jnl`	A Mixture Model and Task Allocation Scheme for Crowdsourcing. CoRR Irineo Cabreros, Karan Singh, Angela Zhou