Graduated Non-Convexity

SHIFT estimator improves robust double machine learning for heavy-tailed data

Researchers have developed SHIFT, a new robust estimator for Double Machine Learning (DML) pipelines designed to handle heavy-tailed data contamination. SHIFT combines cross-fit nuisance orthogonalization with a kernel-…