Alpha-Stable Matrix Factorization
Identifieur interne : 000C23 ( Hal/Curation ); précédent : 000C22; suivant : 000C24Alpha-Stable Matrix Factorization
Auteurs : Umut Simsekli [Turquie] ; Antoine Liutkus [France] ; Taylan Cemgil [Turquie]Source :
- IEEE Signal Processing Letters [ 1070-9908 ] ; 2015-09.
English descriptors
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.
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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.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Alpha-Stable Matrix Factorization</title><author role="aut"><persName><forename type="first">Umut</forename><surname>Simsekli</surname></persName><email></email><idno type="idhal">umut-simsekli</idno><idno type="halauthor">1209479</idno><idno type="arXiv">http://arxiv.org/a/Simsekli_U</idno><orgName ref="#struct-322536"></orgName><affiliation ref="#struct-253597"></affiliation></author><author role="aut"><persName><forename type="first">Antoine</forename><surname>Liutkus</surname></persName><email>antoine@liutkus.net</email><ptr type="url" target="http://www.enst.fr/~liutkus/"></ptr><idno type="idhal">antoine-liutkus</idno><idno type="halauthor">661657</idno><affiliation ref="#struct-420403"></affiliation></author><author role="aut"><persName><forename type="first">Taylan</forename><surname>Cemgil</surname></persName><email>taylan.cemgil@boun.edu.tr</email><idno type="halauthor">1209480</idno><affiliation ref="#struct-253597"></affiliation></author><editor role="depositor"><persName><forename>Antoine</forename><surname>Liutkus</surname></persName><email>antoine@liutkus.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2015-09-06 11:12:25</date><date type="whenWritten">2015</date><date type="whenModified">2015-09-21 11:23:08</date><date type="whenReleased">2015-09-07 13:42:54</date><date type="whenProduced">2015-09</date><date type="whenEndEmbargoed">2015-09-06</date><ref type="file" target="https://hal.inria.fr/hal-01194354/document"><date notBefore="2015-09-06"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/hal-01194354/file/simsekli_alpha_NMF_2015.pdf"><date notBefore="2015-09-06"></date></ref></edition><respStmt><resp>contributor</resp><name key="153135"><persName><forename>Antoine</forename><surname>Liutkus</surname></persName><email>antoine@liutkus.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-01194354</idno><idno type="halUri">https://hal.inria.fr/hal-01194354</idno><idno type="halBibtex">simsekli:hal-01194354</idno><idno type="halRefHtml">IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2015, pp.5</idno><idno type="halRef">IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2015, pp.5</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Alpha-Stable Matrix Factorization</title><author role="aut"><persName><forename type="first">Umut</forename><surname>Simsekli</surname></persName><idno type="idHal">umut-simsekli</idno><idno type="halAuthorId">1209479</idno><idno type="arXiv">http://arxiv.org/a/Simsekli_U</idno><orgName ref="#struct-322536"></orgName><affiliation ref="#struct-253597"></affiliation></author><author role="aut"><persName><forename type="first">Antoine</forename><surname>Liutkus</surname></persName><email>antoine@liutkus.net</email><ptr type="url" target="http://www.enst.fr/~liutkus/"></ptr><idno type="idHal">antoine-liutkus</idno><idno type="halAuthorId">661657</idno><affiliation ref="#struct-420403"></affiliation></author><author role="aut"><persName><forename type="first">Taylan</forename><surname>Cemgil</surname></persName><email>taylan.cemgil@boun.edu.tr</email><idno type="halAuthorId">1209480</idno><affiliation ref="#struct-253597"></affiliation></author></analytic><monogr><idno type="halJournalId" status="VALID">5350</idno><idno type="issn">1070-9908</idno><title level="j">IEEE Signal Processing Letters</title><imprint><publisher>Institute of Electrical and Electronics Engineers</publisher><biblScope unit="pp">5</biblScope><date type="datePub">2015-09</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Matrix factorization</term><term xml:lang="en">Stable distributions</term><term xml:lang="en">Markov Chain Monte Carlo</term></keywords><classCode scheme="halDomain" n="info.info-ts">Computer Science [cs]/Signal and Image Processing</classCode><classCode scheme="halTypology" n="ART">Journal articles</classCode></textClass><abstract xml:lang="en">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.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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