activity
20192026
most citedLocalization in 1D non-parametric latent space models from pairwise affinities

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

collaborators

7 papers

math.ST2026

On the privacy cost for dependent Gaussian data: spectral density estimation under local differential privacy

Yann Issartel, François Roueff

We study the fundamental problem of estimating the dependence structure of a centered stationary Gaussian process under local differential privacy (LDP). In this setting, the spect…

stat.ML2026

Active Seriation: Efficient Ordering Recovery with Statistical Guarantees

James Cheshire, Yann Issartel

Active seriation aims at recovering an unknown ordering of items by adaptively querying pairwise similarities. The observations are noisy measurements of entries of an underlyi…

math.ST2024

Minimax optimal seriation in polynomial time

Yann Issartel, Christophe Giraud, Nicolas Verzelen

We consider the seriation problem, whose goal is to recover a hidden ordering from a noisy observation of a permuted Robinson matrix. We establish sharp minimax rates under average…

math.ST2021★ 1 cited

Localization in 1D non-parametric latent space models from pairwise affinities

Christophe Giraud, Yann Issartel, Nicolas Verzelen

We consider the problem of estimating latent positions in a one-dimensional torus from pairwise affinities. The observed affinity between a pair of items is modeled as a noisy obse…

math.ST2021★ 1 cited

Locally differentially private estimation of nonlinear functionals of discrete distributions

Cristina Butucea, Yann Issartel

We study the problem of estimating non-linear functionals of discrete distributions in the context of local differential privacy. The initial data are supp…

stat.ML2019

On the Estimation of Network Complexity: Dimension of Graphons

Yann Issartel

Network complexity has been studied for over half a century and has found a wide range of applications. Many methods have been developed to characterize and estimate the complexity…

stat.ML2019★ 1 cited

Pair-Matching: Links Prediction with Adaptive Queries

Christophe Giraud, Yann Issartel, Luc Lehéricy +1

The pair-matching problem appears in many applications where one wants to discover good matches between pairs of entities or individuals. Formally, the set of individuals is repres…