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stat.ME2024
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
Michael Lingzhi Li, Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework…
cs.LG2024
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…