Titre :

On variable splitting for Markov chain Monte Carlo

Auteur(s) :

Vono, Maxime [Auteur]
Signal et Communications [IRIT-SC]
Dobigeon, Nicolas [Auteur]
Signal et Communications [IRIT-SC]
Institut National Polytechnique (Toulouse) [Toulouse INP]
Chainais, Pierre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Titre de la manifestation scientifique :

Workshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS 2019)

Ville :

Toulouse

Pays :

France

Date de début de la manifestation scientifique :

2019-04-01

Titre de l’ouvrage :

Proceedings of SPARS 2019

Date de publication :

2019

Mot(s)-clé(s) en anglais :

Markov chain Monte Carlo(MCMC) algorithms

Discipline(s) HAL :

Informatique [cs]/Traitement du signal et de l'image [eess.SP]

Résumé en anglais : [en]

Variable splitting is an old but widely used technique whichaims at dividing an initial complicated optimization problem into simplersub-problems. In this work, we take inspiration from this variable splitting idea in order ...
Lire la suite >Variable splitting is an old but widely used technique whichaims at dividing an initial complicated optimization problem into simplersub-problems. In this work, we take inspiration from this variable splitting idea in order to build efficient Markov chain Monte Carlo(MCMC) algorithms. Starting from an initial complex target distribution,auxiliary variables are introduced such that the marginal distributionof interest matches the initial one asymptotically. In addition to havetheoretical guarantees, the benefits of such an asymptotically exact dataaugmentation (AXDA) are fourfold: (i) easier-to-sample full conditionaldistributions, (ii) possibility to embed while accelerating state-of-the-artMCMC approaches, (iii) possibility to distribute the inference and (iv)to respect data privacy issues. The proposed approach is illustrated onclassical image processing and statistical learning problems.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Nationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL