Low rank approximation of a set of matrices

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present dynamical systems for computing the low rank approximation of a single matrix and of a set of matrices. These dynamical systems arise from solving an optimization problem involving these matrices. The proposed methods are based on applying smooth optimization techniques on smooth manifolds. Many of these systems are then modified to obtain power-like methods for computing a few dominant singular triplets of large matrices simultaneously.

Original languageEnglish (US)
Title of host publicationISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
Subtitle of host publicationNano-Bio Circuit Fabrics and Systems
Pages3517-3520
Number of pages4
DOIs
StatePublished - Aug 31 2010
Event2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France
Duration: May 30 2010Jun 2 2010

Publication series

NameISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

Other

Other2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
CountryFrance
CityParis
Period5/30/106/2/10

Keywords

  • Constrained optimization
  • Low-rank matrix approximation of multiple matrices
  • Principal singular flow
  • Singular value decomposition
  • Stiefel manifold

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