A distance-based batch active learning criterion that simultaneously promotes diversity and treated-control similarity reduces PEHE in causal effect estimation under limited labeling budgets, per experiments on IHDP, IBM, and CMNIST.
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Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation
A distance-based batch active learning criterion that simultaneously promotes diversity and treated-control similarity reduces PEHE in causal effect estimation under limited labeling budgets, per experiments on IHDP, IBM, and CMNIST.