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dc.contributor.authorDutta, Aritra
dc.contributor.authorHanzely, Filip
dc.contributor.authorLiang, Jingwei
dc.contributor.authorRichtarik, Peter
dc.date.accessioned2020-07-22T11:25:21Z
dc.date.available2019-11-27T11:06:16Z
dc.date.available2020-07-22T11:25:21Z
dc.date.issued2020-07-21
dc.identifier.citationDutta, A., Hanzely, F., Liang, J., & Richtarik, P. (2020). Best Pair Formulation & Accelerated Scheme for Non-Convex Principal Component Pursuit. IEEE Transactions on Signal Processing, 68, 6128–6141. doi:10.1109/tsp.2020.3011024
dc.identifier.issn1941-0476
dc.identifier.doi10.1109/TSP.2020.3011024
dc.identifier.urihttp://hdl.handle.net/10754/660274
dc.description.abstractGiven two disjoint sets, the best pair problem aims to find a point in one set and another point in the other set with minimal distance between them. In this paper, we formulate the classical robust principal component analysis (RPCA) problem as a best pair problem and design an accelerated proximal gradient algorithm to solve it. We prove that the method enjoys global convergence with a local linear rate. Our extensive numerical experiments on both real and synthetic data sets suggest that our proposed algorithm outperforms relevant baseline algorithms in the literature.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/9145595/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9145595
dc.rightsArchived with thanks to IEEE Transactions on Signal Processing
dc.subjectPrincipal component analysis
dc.subjectPrincipal component pursuit
dc.subjectRobust PCA
dc.subjectLow-rank and sparse matrix decomposition
dc.subjectMatrix completion
dc.subjectVideo segmentation
dc.subjectOptimization
dc.subjectNon-convex robust PCA
dc.subjectAccelerated proximal gradient
dc.titleBest Pair Formulation & Accelerated Scheme for Non-convex Principal Component Pursuit
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer Science Program
dc.identifier.journalIEEE Transactions on Signal Processing
dc.eprint.versionPost-print
dc.contributor.institutionUniversity of Cambridge, 2152 Cambridge United Kingdom of Great Britain and Northern Ireland CB3 0WA
dc.identifier.arxivid1905.10598
kaust.personDutta, Aritra
kaust.personHanzely, Filip
kaust.personRichtarik, Peter
refterms.dateFOA2019-11-27T11:07:15Z
dc.date.published-online2020-07-21
dc.date.published-print2020
dc.date.posted2019-05-25


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