activity
20072025
most citedPECOK: a convex optimization approach to variable clustering

13 citations · 48 across the 24 of their papers we have counts for

collaborators

36 papers

stat.ML2025

Model-free algorithms for fast node clustering in SBM type graphs and application to social role inference in animals

Bertrand Cloez, Adrien Cotil, Jean-Baptiste Menassol +1

We propose a novel family of model-free algorithms for node clustering and parameter inference in graphs generated from the Stochastic Block Model (SBM), a fundamental framework in…

math.ST2023

Optimal rates for ranking a permuted isotonic matrix in polynomial time

Emmanuel Pilliat, Alexandra Carpentier, Nicolas Verzelen

We consider a ranking problem where we have noisy observations from a matrix with isotonic columns whose rows have been permuted by some permutation *. This encompasses many mo…

stat.ML2023★ 2 cited

Active Ranking of Experts Based on their Performances in Many Tasks

El Mehdi Saad, Nicolas Verzelen, Alexandra Carpentier

We consider the problem of ranking n experts based on their performances on d tasks. We make a monotonicity assumption stating that for each pair of experts, one outperforms the ot…

stat.ML2023

Covariance Adaptive Best Arm Identification

El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen

We consider the problem of best arm identification in the multi-armed bandit model, under fixed confidence. Given a confidence input , the goal is to identify the arm with the h…

math.ST2022★ 1 cited

Optimal Permutation Estimation in Crowd-Sourcing problems

Emmanuel Pilliat, Alexandra Carpentier, Nicolas Verzelen

Motivated by crowd-sourcing applications, we consider a model where we have partial observations from a bivariate isotonic n x d matrix with an unknown permutation * acting on…

math.ST2021

Optimal Estimation of Schatten Norms of a rectangular Matrix

Solène Thépaut, Nicolas Verzelen

We consider the twin problems of estimating the effective rank and the Schatten norms of a rectangular matrix from noisy observations. When…