79 citations · 312 across the 15 of their papers we have counts for
7 papers · 1 filter
A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret
Connor Lawless, Angela Zhou
In this short technical note we propose a baseline for decision-aware learning for contextual linear optimization, which solves stochastic linear optimization when cost coefficient…
Off-Policy Evaluation with Policy-Dependent Optimization Response
Wenshuo Guo, Michael I. Jordan, Angela Zhou
The intersection of causal inference and machine learning for decision-making is rapidly expanding, but the default decision criterion remains an \textit{average} of individual cau…
Stateful Offline Contextual Policy Evaluation and Learning
Nathan Kallus, Angela Zhou
We study off-policy evaluation and learning from sequential data in a structured class of Markov decision processes that arise from repeated interactions with an exogenous sequence…
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning
Nathan Kallus, Angela Zhou
Off-policy evaluation of sequential decision policies from observational data is necessary in applications of batch reinforcement learning such as education and healthcare. In such…
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric
Nathan Kallus, Angela Zhou
Where machine-learned predictive risk scores inform high-stakes decisions, such as bail and sentencing in criminal justice, fairness has been a serious concern. Recent work has cha…
Confounding-Robust Policy Improvement
Nathan Kallus, Angela Zhou
We study the problem of learning personalized decision policies from observational data while accounting for possible unobserved confounding. Previous approaches, which assume unco…
Dynamic Task Allocation for Crowdsourcing Settings
Angela Zhou, Irineo Cabreros, Karan Singh
We consider the problem of optimal budget allocation for crowdsourcing problems, allocating users to tasks to maximize our final confidence in the crowdsourced answers. Such an opt…