2 papers
cs.LG2025
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…
cs.LG2024
Bayesian Safe Policy Learning with Chance Constrained Optimization: Application to Military Security Assessment during the Vietnam War
Zeyang Jia, Eli Ben-Michael, Kosuke Imai
Algorithmic decisions and recommendations are used in many high-stakes decision-making settings such as criminal justice, medicine, and public policy. We investigate whether it wou…