Angela Zhou | DeepAI

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Featured Co-authors

Michael I. Jordan
283 publications
Nathan Kallus
88 publications
Karan Singh
34 publications
Suresh Venkatasubramanian
29 publications
Wenshuo Guo
21 publications
Xiaojie Mao
18 publications
Brian Brubach
14 publications
Kristian Lum
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Connor Lawless
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David Bruns-Smith
4 publications
Aaron Horowitz
4 publications

∙ 09/12/2023

Optimal and Fair Encouragement Policy Evaluation and Learning

In consequential domains, it is often impossible to compel individuals t...

0 Angela Zhou, et al. ∙

∙ 02/01/2023

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

Offline reinforcement learning is important in domains such as medicine,...

0 David Bruns-Smith, et al. ∙

∙ 11/09/2022

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

In this short technical note we propose a baseline for decision-aware le...

0 Connor Lawless, et al. ∙

∙ 02/25/2022

Off-Policy Evaluation with Policy-Dependent Optimization Response

The intersection of causal inference and machine learning for decision-m...

1 Wenshuo Guo, et al. ∙

∙ 11/16/2021

An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls

We conduct an empirical evaluation of the impact of New York's bail refo...

0 Angela Zhou, et al. ∙

∙ 10/19/2021

Stateful Offline Contextual Policy Evaluation and Learning

We study off-policy evaluation and learning from sequential data in a st...

0 Nathan Kallus, et al. ∙

∙ 06/10/2021

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

Risk assessment instrument (RAI) datasets, particularly ProPublica's COM...

0 Michelle Bao, et al. ∙

∙ 12/21/2020

Fairness, Welfare, and Equity in Personalized Pricing

We study the interplay of fairness, welfare, and equity considerations i...

0 Nathan Kallus, et al. ∙

∙ 02/11/2020

Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning

Off-policy evaluation of sequential decision policies from observational...

8 Nathan Kallus, et al. ∙

∙ 06/04/2019

Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds

Personalized interventions in social services, education, and healthcare...

0 Nathan Kallus, et al. ∙

∙ 06/01/2019

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

The increasing impact of algorithmic decisions on people's lives compels...

0 Nathan Kallus, et al. ∙

∙ 02/15/2019

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

Where machine-learned predictive risk scores inform high-stakes decision...

0 Nathan Kallus, et al. ∙

∙ 10/05/2018

Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding

We study the problem of learning conditional average treatment effects (...

0 Nathan Kallus, et al. ∙

∙ 06/07/2018

Residual Unfairness in Fair Machine Learning from Prejudiced Data

Recent work in fairness in machine learning has proposed adjusting for f...

0 Nathan Kallus, et al. ∙

∙ 05/22/2018

Confounding-Robust Policy Improvement

We study the problem of learning personalized decision policies from obs...

0 Nathan Kallus, et al. ∙

∙ 02/16/2018

Policy Evaluation and Optimization with Continuous Treatments

We study the problem of policy evaluation and learning from batched cont...

0 Nathan Kallus, et al. ∙

∙ 01/30/2017

Dynamic Task Allocation for Crowdsourcing Settings

We consider the problem of optimal budget allocation for crowdsourcing p...

0 Angela Zhou, et al. ∙

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