A model-agnostic conformal selection method reformulates CATE-based beneficiary identification as multiple testing with RCT-calibrated p-values and FDR control, allowing external data for model training.
Advances in Neural Information Processing Systems , volume=
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Standard conformal prediction gives nominal overall coverage on Pew survey data but leaves ~13-point weighted gaps across race-education subgroups, and group-specific Mondrian calibration does not reliably close them.
citing papers explorer
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A Conformal Selection Framework for Individual Treatment Beneficiaries with Auxiliary External Data
A model-agnostic conformal selection method reformulates CATE-based beneficiary identification as multiple testing with RCT-calibrated p-values and FDR control, allowing external data for model training.
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Socio-Conformal Calibration in Complex Survey Data: Marginal Validity Is Not Enough for Subgroup Reliability
Standard conformal prediction gives nominal overall coverage on Pew survey data but leaves ~13-point weighted gaps across race-education subgroups, and group-specific Mondrian calibration does not reliably close them.