136 citations
- Laboratoire de Mathématiques d'OrsayFR6 papers
- Centre Inria de SaclayFR3 papers
- Université Paris-SaclayFR3 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Cancer et génome: Bioinformatique, biostatistiques et épidémiologie des systèmes complexes1 paper
- Centre de Mathématiques Appliquées de l'École polytechniqueFR1 paper
- Centre de Recherche en Économie et StatistiqueFR1 paper
- Centre de Recherche en Mathématiques de la DécisionFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Département de mathématiques et applicationsFR1 paper
- École Normale Supérieure - PSLFR1 paper
- École PolytechniqueFR1 paper
9 papers
Nonparametric method for space conditional density estimation in moderately large dimensions
Minh-Lien Jeanne Nguyen
In this paper, we consider the problem of estimating a conditional density in moderately large dimensions. Much more informative than regression functions, conditional densities ar…
Cross-validation improved by aggregation: Agghoo
Guillaume Maillard, Sylvain Arlot, Matthieu Lerasle
Cross-validation is widely used for selecting among a family of learning rules. This paper studies a related method, called aggregated hold-out (Agghoo), which mixes cross-validati…
Empirical Bayes approaches to PageRank type algorithms for rating scientific journals
Jean-Louis Foulley, Gilles Celeux, Julie Josse
Following criticisms against the journal Impact Factor, new journal influence scores have been developed such as the Eigenfactor or the Prestige Scimago Journal Rank. They are base…
Cross-validation
Sylvain Arlot
This text is a survey on cross-validation. We define all classical cross-validation procedures, and we study their properties for two different goals: estimating the risk of a give…
The Statistical Performance of Collaborative Inference
Gérard Biau, Kevin Bleakley, Benoit Cadre
The statistical analysis of massive and complex data sets will require the development of algorithms that depend on distributed computing and collaborative inference. Inspired by t…
Finite mixture regression: A sparse variable selection by model selection for clustering
Emilie Devijver
We consider a finite mixture of Gaussian regression model for high- dimensional data, where the number of covariates may be much larger than the sample size. We propose to estimate…