Clément Levrard

Research fields

• Clustering/Unsupervised learning
• Topological and Geometric Inference

Publications

• 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 , to appear in Bernoulli Journal
• 2022: E. Aamari, C. Berenfeld et C. Levrard, Optimal Reach Estimation and Metric Learning , to appear in The Annals of Statistics

Preprints, reports

• 2014: C. Levrard, Quantification vectorielle en grande dimension: vitesses de convergence et sélection de variables , PhD manuscript, advised by P.Massart et G.Biau , defended on 2014, September 30th.
• 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 , "Habilitation à diriger des recherches" manuscript, defended on 2022, December 5th.

Current students

• 2020 - Olympio Hacquard (co-advised by G. Blanchard)
• 2022 - Arthur Stéphanovitch (co-advised by Eddie Aamari)

Awards

• Prix Marie-Jeanne Laurent Duhamel 2017 from the SFDS (French Statistician Society).