Winsorized mean estimation with heavy tails and adversarial contamination
Statistics Theory
2026-03-27 v3 Statistics Theory
Abstract
Finite-sample upper bounds on the estimation error of a winsorized mean estimator of the population mean in the presence of heavy tails and adversarial contamination are established. In comparison to existing results, the winsorized mean estimator we study avoids a sample splitting device and winsorizes substantially fewer observations, which improves its applicability and practical performance.
Keywords
Cite
@article{arxiv.2504.08482,
title = {Winsorized mean estimation with heavy tails and adversarial contamination},
author = {Anders Bredahl Kock and David Preinerstorfer},
journal= {arXiv preprint arXiv:2504.08482},
year = {2026}
}