The group fused Lasso for multiple change-point detection

Kevin Bleakley 1 Jean-Philippe Vert 2, 3, *
* Auteur correspondant
1 SELECT - Model selection in statistical learning
Inria Saclay - Ile de France, LMO - Laboratoire de Mathématiques d'Orsay, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : We present the group fused Lasso for detection of multiple change-points shared by a set of co-occurring one-dimensional signals. Change-points are detected by approximating the original signals with a constraint on the multidimensional total variation, leading to piecewise-constant approximations. Fast algorithms are proposed to solve the resulting optimization problems, either exactly or approximately. Conditions are given for consistency of both algorithms as the number of signals increases, and empirical evidence is provided to support the results on simulated and array comparative genomic hybridization data.
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-00602121
Contributeur : Jean-Philippe Vert <>
Soumis le : mardi 21 juin 2011 - 15:27:22
Dernière modification le : mercredi 6 février 2019 - 10:20:46
Document(s) archivé(s) le : jeudi 22 septembre 2011 - 02:25:54

Fichiers

techreport.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00602121, version 1
  • ARXIV : 1106.4199

Collections

Citation

Kevin Bleakley, Jean-Philippe Vert. The group fused Lasso for multiple change-point detection. 2011. 〈hal-00602121〉

Partager

Métriques

Consultations de la notice

1473

Téléchargements de fichiers

1724