54 citations · 180 across the 26 of their papers we have counts for
4 papers · 1 filter
Robust machine learning by median-of-means : theory and practice
Guillaume Lecué, Matthieu Lerasle
We introduce new estimators for robust machine learning based on median-of-means (MOM) estimators of the mean of real valued random variables. These estimators achieve optimal rate…
Cross-validation improved by aggregation: Agghoo
Guillaume Maillard, Sylvain Arlot, Matthieu Lerasle
Cross-validation is widely used for selecting among a family of learning rules. This paper studies a related method, called aggregated hold-out (Agghoo), which mixes cross-validati…
Learning the distribution of latent variables in paired comparison models with round-robin scheduling
Roland Diel, Sylvain Le Corff, Matthieu Lerasle
Paired comparison data considered in this paper originate from the comparison of a large number N of individuals in couples. The dataset is a collection of results of contests betw…
Learning from MOM's principles: Le Cam's approach
Lecué Guillaume, Lerasle Matthieu
We obtain estimation error rates for estimators obtained by aggregation of regularized median-of-means tests, following a construction of Le Cam. The results hold with exponentiall…