InforLorV4, Main, Exploration, bibRecord, 000357

Alpha-Stable Matrix Factorization

Identifieur interne : 000357 ( Main/Exploration ); précédent : 000356; suivant : 000358

Alpha-Stable Matrix Factorization

Auteurs : Umut Simsekli [Turquie] ; Antoine Liutkus [France] ; Taylan Cemgil [Turquie]

Source :

IEEE Signal Processing Letters [ 1070-9908 ] ; 2015-09.

RBID : Hal:hal-01194354

English descriptors

mix :
- Markov Chain Monte Carlo, Matrix factorization, Stable distributions.

Abstract

Matrix factorization (MF) models have been widely used in data analysis. Even though they have been shown to be useful in many applications, classical MF models often fall short when the observed data are impulsive and contain outliers. In this study, we present αMF, a MF model with α-stable observations. Stable distributions are a family of heavy-tailed distributions that is particularly suited for such impulsive data. We develop a Markov Chain Monte Carlo method, namely a Gibbs sampler, for making inference in the model. We evaluate our model on both synthetic and real audio applications. Our experiments on speech enhancement show that αMF yields superior performance to a popular audio processing model in terms of objective measures. Furthermore, αMF provides a theoretically sound justification for recent empirical results obtained in audio processing.

Url:

https://hal.inria.fr/hal-01194354

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Hal, to step Corpus: 000C23
to stream Hal, to step Curation: 000C23
to stream Hal, to step Checkpoint: 000336
to stream Main, to step Merge: 000360
to stream Main, to step Curation: 000357

Le document en format XML

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   |texte=   Alpha-Stable Matrix Factorization
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Alpha-Stable Matrix Factorization

Alpha-Stable Matrix Factorization

Source :

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri