97 citations
- Laboratoire de Probabilités et Modèles AléatoiresFR238 papers
- Sorbonne UniversitéFR182 papers
- Centre National de la Recherche ScientifiqueFR143 papers
- Université Paris CitéFR90 papers
- Sorbonne Paris CitéFR46 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR29 papers
- École Normale Supérieure - PSLFR28 papers
- Laboratoire de Mathématiques d'OrsayFR28 papers
- Département de mathématiques et applicationsFR25 papers
- École PolytechniqueFR24 papers
- Institut Universitaire de FranceFR23 papers
- Université Paris DiderotFR23 papers
67 papers · 1 filter
Consistent model selection in a collection of stochastic block models
Lucie Arts
We introduce the penalized Krichevsky-Trofimov (KT) estimator as a convergent method for estimating the number of nodes clusters when observing multiple networks within both multi-…
On the Asymptotics of Importance Weighted Variational Inference
Badr-Eddine Cherief-Abdellatif, Randal Douc, Arnaud Doucet +1
For complex latent variable models, the likelihood function is not available in closed form. In this context, a popular method to perform parameter estimation is Importance Weighte…
Nonparametric estimation of the stationary density for Hawkes-diffusion systems with known and unknown intensity
Chiara Amorino, Charlotte Dion-Blanc, Arnaud Gloter +1
We investigate the nonparametric estimation problem of the density , representing the stationary distribution of a two-dimensional system $\left(Z_t\right)_{t \in[0, T]}=\left(X…
Asymptotics for conformal inference
Ulysse Gazin
Conformal inference is a versatile tool for building prediction sets in regression or classification. We study the false coverage proportion (FCP) in a simultaneous inference setti…
A primer on linear classification with missing data
Angel D Reyero Lobo, Alexis Ayme, Claire Boyer +1
Supervised learning with missing data aims at building the best prediction of a target output based on partially-observed inputs. Major approaches to address this problem can be de…
Online and Offline Robust Multivariate Linear Regression
Antoine Godichon-Baggioni, Stephane S. Robin, Laure Sansonnet
We consider the robust estimation of the parameters of multivariate Gaussian linear regression models. To this aim we consider robust version of the usual (Mahalanobis) least-squar…