activity
20182024
most citedOptimal Reach Estimation and Metric Learning

3 citations · 6 across the 5 of their papers we have counts for

collaborators

6 papers

math.ST2024

A theory of stratification learning

Eddie Aamari, Clément Berenfeld

Given i.i.d. sample from a stratified mixture of immersed manifolds of different dimensions, we study the minimax estimation of the underlying stratified structure. We provide a co…

math.ST2023

Theoretical Foundations of Ordinal Multidimensional Scaling, Including Internal and External Unfolding

Ery Arias-Castro, Clément Berenfeld, Daniel Kane

We provide a comprehensive theory of multiple variants of ordinal multidimensional scaling,including internal unfolding and external unfolding. We first follow Shepard (1966) and w…

math.ST2022★ 3 cited

Optimal Reach Estimation and Metric Learning

Eddie Aamari, Clément Berenfeld, Clément Levrard

We study the estimation of the reach, an ubiquitous regularity parameter in manifold estimation and geometric data analysis. Given an i.i.d. sample over an unknown -dimensional…

math.ST2022★ 3 cited

Estimating a density near an unknown manifold: a Bayesian nonparametric approach

Clément Berenfeld, Paul Rosa, Judith Rousseau

We study the Bayesian density estimation of data living in the offset of an unknown submanifold of the Euclidean space. In this perspective, we introduce a new notion of anisotropi…

math.ST2021

The Coreness and H-Index of Random Geometric Graphs

Eddie Aamari, Ery Arias-Castro, Clément Berenfeld

In network analysis, a measure of node centrality provides a scale indicating how central a node is within a network. The coreness is a popular notion of centrality that accounts f…

math.PR2018

Some Random Paths with Angle Constraints

Clément Berenfeld, Ery Arias-Castro

We propose a simple, geometrically-motivated construction of smooth random paths in the plane. The construction is such that, with probability one, the paths have finite curvature…