Computing eigenelements of real symmetric matrices via optimization

DOI10.1023/B:COAP.0000044182.33308.82zbMath1062.90071MaRDI QIDQ1771219

Xianqiang Yang

Publication date: 7 April 2005

Published in: Computational Optimization and Applications (Search for Journal in Brave)

zbMATH Keywords

variational principlesLanczos methodgeneralized eigenproblemlimited-memory algorithmsNewton-type algorithms

Mathematics Subject Classification ID

Methods of quasi-Newton type (90C53) Iterative numerical methods for linear systems (65F10)

Related Items (7)

A limited memory BFGS algorithm for non-convex minimization with applications in matrix largest eigenvalue problem ⋮ The symmetric eigenvalue complementarity problem ⋮ A DC programming approach for solving the symmetric eigenvalue complementarity problem ⋮ On the solution of the symmetric eigenvalue complementarity problem by the spectral projected gradient algorithm ⋮ Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization ⋮ Continuous methods for symmetric generalized eigenvalue problems ⋮ Barzilai-Borwein-like methods for the extreme eigenvalue problem

Uses Software

• L-BFGS
• JDQR
• JDQZ

This page was built for publication: Computing eigenelements of real symmetric matrices via optimization