A Block Coordinate Descent Method for Multi-Convex Optimization with Applications to Nonnegative Tensor Factorization and Completion

Simple item page
dc.contributor.authorXu, Yangyangen_US
dc.contributor.authorYin, Wotaoen_US
dc.date.accessioned2018-06-19T17:48:00Zen_US
dc.date.available2018-06-19T17:48:00Zen_US
dc.date.issued2012-08en_US
dc.date.noteAugust 2012en_US
dc.description.abstractThis paper considers block multi-convex optimization, where the feasible set and objective function are generally non-convex but convex in each block of variables. We review some of its interesting examples and propose a generalized block coordinate descent method. Under certain conditions, we show that any limit point satisfies the Nash equilibrium conditions. Furthermore, we establish its global convergence and estimate its asymptotic convergence rate by assuming a property based on the Kurdyka-Lojasiewicz inequality. The proposed algorithms are adapted for factorizing nonnegative matrices and tensors, as well as completing them from their incomplete observations. The algorithms were tested on synthetic data, hyperspectral data, as well as image sets from the CBCL and ORL databases. Compared to the existing state-of-the-art algorithms, the proposed algorithms demonstrate superior performance in both speed and solution quality. The Matlab code is available for download from the authors' homepages.en_US
dc.format.extent32 ppen_US
dc.identifier.citationXu, Yangyang and Yin, Wotao. "A Block Coordinate Descent Method for Multi-Convex Optimization with Applications to Nonnegative Tensor Factorization and Completion." (2012) <a href="https://hdl.handle.net/1911/102204">https://hdl.handle.net/1911/102204</a>.en_US
dc.identifier.digitalTR12-15en_US
dc.identifier.urihttps://hdl.handle.net/1911/102204en_US
dc.language.isoengen_US
dc.titleA Block Coordinate Descent Method for Multi-Convex Optimization with Applications to Nonnegative Tensor Factorization and Completionen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
TR12-15.PDF
Size:
459.87 KB
Format:
Adobe Portable Document Format
Download
Collections
CMOR Technical Reports