Non-asymptotic oracle inequalities for the Lasso and Group Lasso in high dimensional logistic model - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue ESAIM: Probability and Statistics Année : 2016

Non-asymptotic oracle inequalities for the Lasso and Group Lasso in high dimensional logistic model

Résumé

We consider the problem of estimating a function f(0) in logistic regression model. We propose to estimate this function f(0) by a sparse approximation build as a linear combination of elements of a given dictionary of p functions. This sparse approximation is selected by the Lasso or Group Lasso procedure. In this context, we state non asymptotic oracle inequalities for Lasso and Group Lasso under restricted eigenvalue assumption as introduced in [P.J. Bickel, Y. Ritov and A.B. Tsybakov, Ann. Statist. 37 (2009) 1705-1732].
Fichier principal
Vignette du fichier
Kwemou_2016_ESAIM Prob Stat_1.pdf (359.76 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01601407 , version 1 (27-05-2020)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Marius Kwemou. Non-asymptotic oracle inequalities for the Lasso and Group Lasso in high dimensional logistic model. ESAIM: Probability and Statistics, 2016, 20, pp.309-331. ⟨10.1051/ps/2015020⟩. ⟨hal-01601407⟩
66 Consultations
54 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More