1.1k citations · 1.5k across the 17 of their papers we have counts for
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Robust Topological Inference: Distance To a Measure and Kernel Distance
Frédéric Chazal, Brittany T. Fasy, Fabrizio Lecci +3
Let P be a distribution with support S. The salient features of S can be quantified with persistent homology, which summarizes topological features of the sublevel sets of the dist…
Grouped variable importance with random forests and application to multiple functional data analysis
Baptiste Gregorutti, Bertrand Michel, Philippe Saint-Pierre
The selection of grouped variables using the random forest algorithm is considered. First a new importance measure adapted for groups of variables is proposed. Theoretical insights…
Subsampling Methods for Persistent Homology
Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci +3
Persistent homology is a multiscale method for analyzing the shape of sets and functions from point cloud data arising from an unknown distribution supported on those sets. When th…
Improved rates for Wasserstein deconvolution with ordinary smooth error in dimension one
Jérôme Dedecker, Aurélie Fischer, Bertrand Michel
This paper deals with the estimation of a probability measure on the real line from data observed with an additive noise. We are interested in rates of convergence for the Wasserst…
Sparse Bayesian Unsupervised Learning
Stephane Gaiffas, Bertrand Michel
This paper is about variable selection, clustering and estimation in an unsupervised high-dimensional setting. Our approach is based on fitting constrained Gaussian mixture models,…