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Matthieu Lerasle
Matthieu Lerasle
Ensae-CREST
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Title
Cited by
Cited by
Year
Sub-Gaussian mean estimators
L Devroye, M Lerasle, G Lugosi, RI Oliveira
2092016
Robust machine learning by median-of-means: theory and practice
G Lecué, M Lerasle
1802020
Choice of V for V-fold cross-validation in least-squares density estimation
S Arlot, M Lerasle
Journal of Machine Learning Research 17 (208), 1-50, 2016
1342016
Robust empirical mean estimators
M Lerasle, RI Oliveira
arXiv preprint arXiv:1112.3914, 2011
962011
Robust classification via MOM minimization
G Lecué, M Lerasle, T Mathieu
Machine learning 109, 1635-1665, 2020
672020
Selected topics on robust statistical learning theory
M Lerasle
Lecture Notes, 2019
60*2019
Learning from MOM’s principles: Le Cam’s approach
G Lecué, M Lerasle
Stochastic Processes and their applications 129 (11), 4385-4410, 2019
522019
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
512012
Optimal model selection in density estimation
M Lerasle
Annales de l'IHP Probabilités et statistiques 48 (3), 884-908, 2012
492012
Optimal change-point detection and localization
N Verzelen, M Fromont, M Lerasle, P Reynaud-Bouret
The Annals of Statistics 51 (4), 1586-1610, 2023
442023
Optimal model selection for density estimation of stationary data under various mixing conditions
M Lerasle
372011
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
352019
Robust statistical learning with Lipschitz and convex loss functions
G Chinot, G Lecué, M Lerasle
Probability Theory and related fields 176 (3), 897-940, 2020
342020
On the robustness of the minimum interpolator
G Chinot, M Lerasle
arXiv preprint arXiv:2003.05838, 2020
192020
The number of potential winners in Bradley–Terry model in random environment
R Chetrite, R Diel, M Lerasle
192017
Robust high dimensional learning for Lipschitz and convex losses
C Geoffrey, L Guillaume, L Matthieu
Journal of Machine Learning Research 21 (233), 1-47, 2020
172020
Family-wise separation rates for multiple testing
M Fromont, M Lerasle, P Reynaud-Bouret
172016
Aggregated hold-out
G Maillard, S Arlot, M Lerasle
Journal of Machine Learning Research 22 (20), 1-55, 2021
162021
Statistical learning with Lipschitz and convex loss functions
G Chinot, L Guillaume, L Matthieu
arXiv preprint arXiv:1810.01090, 2018
162018
Markov approximation of chains of infinite order in the -metric
S Gallo, M Lerasle, DY Takahashi
Markov Processes and Related Fields 19 (1), 51--82, 2013
162013
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