Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Parallel Metropolis Chains with Cooperative Adaptation
Year:2016
Research Areas
  • Applications for ingineerings and sciences,
  • Probabilistic theory and procedures,
  • Statistics
Information
Abstract
Monte Carlo methods, such as Markov chain Monte Carlo (MCMC) algorithms, have become very popular in signal processing over the last years. In this work, we introduce a novel MCMC scheme where parallel MCMC chains interact, adapting cooperatively the parameters of their proposal functions. Furthermore, the novel algorithm distributes the computational effort adaptively, rewarding the chains which are providing better performance and, possibly even stopping other ones. These extinct chains can be reactivated if the algorithm considers it necessary. Numerical simulations show the benefits of the novel scheme.
International
Si
Congress
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
960
Place
Shanghai (China)
Reviewers
Si
ISBN/ISSN
978-1-4799-9988-0
10.1109/ICASSP.2016.7472423
Start Date
20/03/2016
End Date
25/03/2016
From page
3974
To page
3978
Proceedings of the 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Participants
  • Autor: Luca Martino (Universidade de Sao Paulo)
  • Autor: Víctor Elvira (Universidad Carlos III de Madrid)
  • Autor: David Luengo Garcia (UPM)
  • Autor: Francisco Louzada (Universidade de Sao Paulo)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Teoría de Aproximación Constructiva y Aplicaciones
  • Departamento: Teoría de la Señal y Comunicaciones (Provisional)
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