Derives closed-form optimal batch sampling probabilities to minimize asymptotic variance of doubly robust ATE estimator with missing outcomes, achieving lower MSE and matching full-sample precision with 75% fewer labels on simulated and real data.
F Additional Lemmas F.1 Results appearing in other works, stated for completeness
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Batch-Adaptive Causal Annotations
Derives closed-form optimal batch sampling probabilities to minimize asymptotic variance of doubly robust ATE estimator with missing outcomes, achieving lower MSE and matching full-sample precision with 75% fewer labels on simulated and real data.