Solving Large-Scale Least Squares Semidefinite Programming by Alternating Direction Methods

The well-known least squares semidefinite programming (LSSDP) problem seeks the nearest adjustment of a given symmetric matrix in the intersection of the cone of positive semidefinite matrices and a set of linear constraints, and it captures many applications in diversing fields. The task of solving...

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Vydáno v:	SIAM journal on matrix analysis and applications Ročník 32; číslo 1; s. 136 - 152
Hlavní autoři:	He, Bingsheng, Xu, Minghua, Yuan, Xiaoming
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2011
Témata:	Algebra Calculus of variations and optimal control Exact sciences and technology Global analysis, analysis on manifolds Intersections Least squares method Linear and multilinear algebra, matrix theory Linear equations Mathematical analysis Mathematical models Mathematical programming Mathematics Matrices Matrix Matrix methods Numerical analysis Numerical analysis. Scientific computation Numerical linear algebra Programming Sciences and techniques of general use Semidefinite programming Studies Tasks Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds Intersection Alternating direction method Cone Solving Least squares problem Square matrix Optimization method 90C06 Semi definite programming least squares semidefinite matrix Constrained optimization Linear constraint Numerical analysis Efficiency Variational inequality Symmetric matrix Least squares method 90C25 90C22 Linear algebra 49M29 Large scale large-scale
ISSN:	0895-4798, 1095-7162
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