Sub-Gaussian mean estimators L Devroye, M Lerasle, G Lugosi, RI Oliveira
190 2016 Robust machine learning by median-of-means: theory and practice G Lecué, M Lerasle
167 2020 Choice of V for V-fold cross-validation in least-squares density estimation S Arlot, M Lerasle
The Journal of Machine Learning Research 17 (1), 7256-7305, 2016
122 2016 Robust empirical mean estimators M Lerasle, RI Oliveira
arXiv preprint arXiv:1112.3914, 2011
92 2011 Robust classification via MOM minimization G Lecué, M Lerasle, T Mathieu
Machine learning 109, 1635-1665, 2020
66 2020 Optimal model selection in density estimation M Lerasle
Annales de l'IHP Probabilités et statistiques 48 (3), 884-908, 2012
51 2012 Learning from MOM’s principles: Le Cam’s approach G Lecué, M Lerasle
Stochastic Processes and their applications 129 (11), 4385-4410, 2019
50 2019 Kernels based tests with non-asymptotic bootstrap approaches for two-sample problems M Fromont, B Laurent, M Lerasle, P Reynaud-Bouret
Conference on Learning Theory, 23.1-23.23, 2012
50 2012 Selected topics on robust statistical learning theory M Lerasle
Lecture Notes, 2019
45 * 2019 Optimal model selection for density estimation of stationary data under various mixing conditions M Lerasle
39 2011 Optimal change-point detection and localization N Verzelen, M Fromont, M Lerasle, P Reynaud-Bouret
The Annals of Statistics 51 (4), 1586-1610, 2023
31 2023 Monk outlier-robust mean embedding estimation by median-of-means M Lerasle, Z Szabó, T Mathieu, G Lecué
International Conference on Machine Learning, 3782-3793, 2019
30 2019 Robust statistical learning with Lipschitz and convex loss functions G Chinot, G Lecué, M Lerasle
Probability Theory and related fields 176 (3-4), 897-940, 2020
29 2020 The number of potential winners in Bradley–Terry model in random environment R Chetrite, R Diel, M Lerasle
18 2017 On the robustness of the minimum G Chinot, M Lerasle
arXiv preprint arXiv:2003.05838, 2020
17 2020 Family-wise separation rates for multiple testing M Fromont, M Lerasle, P Reynaud-Bouret
17 2016 Optimal kernel selection for density estimation M Lerasle, NM Magalhães, P Reynaud-Bouret
High Dimensional Probability VII: The Cargese Volume, 425-460, 2016
16 2016 Aggregated hold-out G Maillard, S Arlot, M Lerasle
The Journal of Machine Learning Research 22 (1), 929-983, 2021
15 2021 Robust high dimensional learning for Lipschitz and convex losses. C Geoffrey, L Guillaume, L Matthieu
The Journal of Machine Learning Research 21 (1), 9483-9529, 2020
15 2020 Markov approximation of chains of infinite order in the S Gallo, M Lerasle, DY Takahashi
Markov Processes and Related Fields 19 (1), 51--82, 2013
15 2013 
Sylvain ArlotUniversité Paris-SaclayGeverifieerd e-mailadres voor universite-paris-saclay.fr
