Titre :

Distributed dictionary learning over a sensor network

Auteur(s) :

Chainais, Pierre [Auteur]
Sequential Learning [SEQUEL]
Centrale Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Richard, Cédric [Auteur]
Joseph Louis LAGRANGE [LAGRANGE]

Titre de la manifestation scientifique :

CaP 2013

Ville :

Villeneuve d'Ascq

Pays :

France

Date de début de la manifestation scientifique :

2013-07-02

Date de publication :

2013-07-02

Mot(s)-clé(s) en anglais :

block coordinate descent
dictionary learning
sparse coding
distributed estimation
diffusion
matrix factorization
adaptive networks
block coordinate descent.

Discipline(s) HAL :

Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Apprentissage [cs.LG]

Résumé en anglais : [en]

We consider the problem of distributed dictionary learning, where a set of nodes is required to collec- tively learn a common dictionary from noisy measure- ments. This approach may be useful in several con- texts including ...
Lire la suite >We consider the problem of distributed dictionary learning, where a set of nodes is required to collec- tively learn a common dictionary from noisy measure- ments. This approach may be useful in several con- texts including sensor networks. Diffusion cooperation schemes have been proposed to solve the distributed linear regression problem. In this work we focus on a diffusion-based adaptive dictionary learning strategy: each node records observations and cooperates with its neighbors by sharing its local dictionary. The resulting algorithm corresponds to a distributed block coordi- nate descent (alternate optimization). Beyond dictio- nary learning, this strategy could be adapted to many matrix factorization problems and generalized to var- ious settings. This article presents our approach and illustrates its efficiency on some numerical examples.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Nationale

Vulgarisation :

Non

Commentaire :

6 pages

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL