A constrained singular value decomposition method that integrates sparsity and orthogonality.

A constrained singular value decomposition method that integrates sparsity and orthogonality.

We propose a new sparsification method for the singular value decomposition-called the constrained singular value decomposition (CSVD)-that can incorporate multiple constraints such as sparsification and orthogonality for the left and right singular vectors. The CSVD can combine different constraint...

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Bibliographic Details
Main Authors: Vincent Guillemot, Derek Beaton, Arnaud Gloaguen, Tommy Löfstedt, Brian Levine, Nicolas Raymond, Arthur Tenenhaus, Hervé Abdi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0211463

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https://doi.org/10.1371/journal.pone.0211463

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