7 citations · 11 across the 4 of their papers we have counts for
5 papers
Optimal robust mean and location estimation via convex programs with respect to any pseudo-norms
Jules Depersin, Guillaume Lecué
We consider the problem of robust mean and location estimation w.r.t. any pseudo-norm of the form where is any symmetric subs…
On the robustness to adversarial corruption and to heavy-tailed data of the Stahel-Donoho median of means
Jules Depersin, Guillaume Lecué
We consider median of means (MOM) versions of the Stahel-Donoho outlyingness (SDO) [stahel 1981, donoho 1982] and of Median Absolute Deviation (MAD) functions to construct subgauss…
A spectral algorithm for robust regression with subgaussian rates
Jules Depersin
We study a new linear up to quadratic time algorithm for linear regression in the absence of strong assumptions on the underlying distributions of samples, and in the presence of o…
Robust subgaussian estimation with VC-dimension
Jules Depersin
Median-of-means (MOM) based procedures provide non-asymptotic and strong deviation bounds even when data are heavy-tailed and/or corrupted. This work proposes a new general way to…
Robust subgaussian estimation of a mean vector in nearly linear time
Jules Depersin, Guillaume Lecué
We construct an algorithm, running in time , which is robust to outliers and heavy-tailed data and which achieves the subgaussian rate from [Lugosi,…