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dc.contributor.authorDutta, Aritra
dc.contributor.authorLi, Xin
dc.date.accessioned2019-01-22T12:37:17Z
dc.date.available2019-01-22T12:37:17Z
dc.date.issued2019-01-03
dc.identifier.citationDutta A, Li X (2018) A Fast Weighted SVT Algorithm. 2018 5th International Conference on Systems and Informatics (ICSAI). Available: http://dx.doi.org/10.1109/icsai.2018.8599289.
dc.identifier.doi10.1109/icsai.2018.8599289
dc.identifier.urihttp://hdl.handle.net/10754/630940
dc.description.abstractSingular value thresholding (SVT) plays an important role in the well-known robust principal component analysis (RPCA) algorithms which have many applications in machine learning, pattern recognition, and computer vision. There are many versions of generalized SVT proposed by researchers to achieve improvement in speed or performance. In this paper, we propose a fast algorithm to solve aweighted singular value thresholding (WSVT) problem as formulated in [1], which uses a combination of the nuclear norm and a weighted Frobenius norm and has shown to be comparable with RPCA method in some real world applications.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8599289
dc.subjectSingular Value Thresholding
dc.subjectLow-rank Approximation
dc.subjectBackground Estimation
dc.titleA Fast Weighted SVT Algorithm
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journal2018 5th International Conference on Systems and Informatics (ICSAI)
dc.contributor.institutionDepartment of Mathematics, University of Central Florida, Orlando, FL, 32816, USA
kaust.personDutta, Aritra
dc.date.published-online2019-01-03
dc.date.published-print2018-11


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