7 papers
Bridging Predictions and Interventions: An Integrated Framework for Automated Decision-Systems
Inioluwa Deborah Raji, Lydia T. Liu, Angela Zhou +27
Automated decision systems (ADS) leverage predictions about individual future outcomes to inform consequential decision-making in organizational settings. Across various settings -…
An Axiomatic Foundation for Decisions with Counterfactual Utility
Benedikt Koch, Kosuke Imai, Tomasz Strzalecki
Counterfactual utilities evaluate decisions not only by the realized outcome under a given decision, but also by the counterfactual outcomes that would arise under alternative deci…
Improving Minority Population Sampling with BISG Probabilities: Evidence from a Survey of Jewish Americans
Kyla Chasalow, Eitan Hersh, Kosuke Imai +1
Sampling geographically dispersed minority populations poses substantial challenges when individual group membership cannot be directly observed. Although stratified sampling can o…
Generalized Sequential Monte Carlo Sampling for Redistricting Simulation
Philip O'Sullivan, Kosuke Imai, Cory McCartan
Simulation methods have become important tools for quantifying partisan and racial bias in redistricting plans. We generalize the Sequential Monte Carlo (SMC) algorithm of McCartan…
Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
Michael Lingzhi Li, Kosuke Imai
Across a wide array of disciplines, many researchers use machine learning (ML) algorithms to identify a subgroup of individuals who are likely to benefit from a treatment the most…
Cramming Contextual Bandits for On-policy Statistical Evaluation
Zeyang Jia, Kosuke Imai, Michael Lingzhi Li
We introduce the cram method as a general statistical framework for evaluating the final learned policy from a multi-armed contextual bandit algorithm, using the dataset generated…