Solving a class of matrix minimization problems by linear variational inequality approaches

Min Tao, Xiaoming YUAN, Bing Sheng He*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A class of matrix optimization problems can be formulated as a linear variational inequalities with special structures. For solving such problems, the projection and contraction method (PC method) is extended to variational inequalities with matrix variables. Then the main costly computational load in PC method is to make a projection onto the semi-definite cone. Exploiting the special structures of the relevant variational inequalities, the Levenberg-Marquardt type projection and contraction method is advantageous. Preliminary numerical tests up to 1000×1000 matrices indicate that the suggested approach is promising.

Original languageEnglish
Pages (from-to)2343-2352
Number of pages10
JournalLinear Algebra and Its Applications
Volume434
Issue number11
DOIs
Publication statusPublished - 1 Jun 2011

Scopus Subject Areas

  • Algebra and Number Theory
  • Numerical Analysis
  • Geometry and Topology
  • Discrete Mathematics and Combinatorics

User-Defined Keywords

  • Matrix minimization
  • Projection and contraction method

Fingerprint

Dive into the research topics of 'Solving a class of matrix minimization problems by linear variational inequality approaches'. Together they form a unique fingerprint.

Cite this