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dc.contributor.authorXu, Yangyang
Yin, Wotao
Wen, Zaiwen
Zhang, Yin
dc.date.accessioned 2018-06-19T17:46:42Z
dc.date.available 2018-06-19T17:46:42Z
dc.date.issued 2011-01
dc.identifier.citation Xu, Yangyang, Yin, Wotao, Wen, Zaiwen, et al.. "An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors." (2011) https://hdl.handle.net/1911/102178.
dc.identifier.urihttps://hdl.handle.net/1911/102178
dc.description.abstract This paper introduces a novel algorithm for the nonnegative matrix factorization and completion problem, which aims to nd nonnegative matrices X and Y from a subset of entries of a nonnegative matrix M so that XY approximates M. This problem is closely related to the two existing problems: nonnegative matrix factorization and low-rank matrix completion, in the sense that it kills two birds with one stone. As it takes advantages of both nonnegativity and low rank, its results can be superior than those of the two problems alone. Our algorithm is applied to minimizing a non-convex constrained least-squares formulation and is based on the classic alternating direction augmented Lagrangian method. Preliminary convergence properties and numerical simulation results are presented. Compared to a recent algorithm for nonnegative random matrix factorization, the proposed algorithm yields comparable factorization through accessing only half of the matrix entries. On tasks of recovering incomplete grayscale and hyperspectral images, the results of the proposed algorithm have overall better qualities than those of two recent algorithms for matrix completion.
dc.format.extent 20 pp
dc.title An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors
dc.type Technical report
dc.date.note January 2011
dc.identifier.digital TR11-03
dc.type.dcmi Text


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