04:00
2026-07-08
machinebrief.com
machine-learning
Heckman-Corrected Epistemic Uncertainty: Selection on Unobservables Defeats Importance Weighting
A new arXiv paper demonstrates that standard importance weighting fails to correct for selection bias in machine learning when selection depends on unobservables correlated with outcomes. The authors …