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Unbiased Treatment Effect Estimation under Network Interference via Neighborhood-Excluded Cross-Fitting
Without interference, cross-fitting enables flexible covariate adjustment while preserving finite-sample unbiasedness under independent unit-level randomization. Under network interference, out-of-sample prediction alone no longer guarantees unbiasedness: assignments entering evaluation-fold Horvitz
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