Clément Levrard

Position actuelle

Professeur
Université de Rennes
IRMAR

Contact

Bureau 304, Bâtiment 22-23
Université de Rennes, Campus de Beaulieu
35042 Rennes cedex
Email: clement[DOT]levrard[AT]univ-rennes1[DOT]fr

Enseignement

Domaines d'intérêt

Clustering, apprentissage non supervisé
Inférence topologique, géométrique

Publications dans les revues à comité de lecture

2011: A. Agarwal, J.C. Duchi, P. Bartlett et C. Levrard, Oracle inequalities for computationally budgeted model selection , COLT 2011 accepted paper
2013: C. Levrard, Fast rates for empirical vector quantization , Electronic Journal of Statistics, Vol.7
2014: C. Levrard, Non-asymptotic bounds for vector quantization in Hilbert spaces, The Annals of Statistics , Vol.43. Supplementary file
2016: C. Levrard, Sparse oracle inequalities for variable selection via regularized quantization , Bernoulli Journal
2017: E. Aamari et C. Levrard, Stability and minimax optimality of Tangential Delaunay Complexes for manifold reconstruction , Discrete and Computational Geometry
2017: E. Aamari et C. Levrard, Non asymptotic rates for manifold, tangent spaces, and curvature estimation , The Annals of Statistics. Supplementary file
2017: C. Levrard, Quantization/Clustering: when and why does k-means work , Journal de la Société Française de Statistiques, Vol.159
2018: C. Brécheteau et C. Levrard, A k-points based distance for robust geometric inference , Bernoulli Journal
2019: C. Brécheteau, A. Fischer et C. Levrard, Robust Bregman Clustering , The Annals of Statistics
2020: M.Royer, F. Chazal, C. Levrard, Y.Ike et Y.Umeda, ATOL: Measure Vectorisation for Automatic Topologically-Oriented Learning , Proceedings of Machine Learning Research
2021: F. Chazal, C. Levrard et M. Royer, Optimal quantization of the mean measure and applications to statistical learning , Electronic Journal of Statistics
2022: O. Hacquard, K. Balasubramian, G. Blanchard, C. Levrard et W. Polonik, Topologically penalized regression on manifolds , Journal of Machine Learning Research
2022: E. Aamari, C. Aaron et C. Levrard, Minimax boundary estimation and estimation with boundary , Bernoulli Journal
2022: E. Aamari, C. Berenfeld et C. Levrard, Optimal Reach Estimation and Metric Learning , The Annals of Statistics
2023: A. Stéphanovitch, E. Aamari et C. Levrard, Wasserstein GANs are Minimax Optimal Distribution Estimators , to appear in The Annals of Statistics
2024: F. Chazal, C. Levrard et M. Royer, Topological Analysis for Detecting Anomalies (TADA) in dependent sequences , to appear in Journal of Machine Learning Research

Preprints, rapports

2014: C. Levrard, Quantification vectorielle en grande dimension: vitesses de convergence et sélection de variables , manuscrit de thèse, effectuée sous la direction de P.Massart et G.Biau , soutenue le 30/09/2014.
2016: G. Biau et C. Levrard, Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data by Yao, F., Wu, Y. and Zou , TEST , Vol. 25, pp. 41-43.
2022: C. Levrard, Distance functions estimation: contributions to support inference and clustering , manuscrit d'Habilitation à diriger des recherches, soutenue le 5/12/2022.
2023: O. Hacquard, G. Blanchard et C. Levrard, Statistical learning on measures: an application to persistence diagrams

Thèses

2020-2023 Olympio Hacquard (co-encadrement avec Gilles Blanchard)
2022 - Arthur Stéphanovitch (co-encadrement avec Eddie Aamari)

Distinctions scientifiques

Prix Marie-Jeanne Laurent Duhamel 2017 de la Société Française de Statistiques.