Structure methods for solving the nearest correlation matrix problem

DOI10.1007/s11117-012-0180-xzbMath1334.90094OpenAlexW2089472575MaRDI QIDQ270046

Suliman Al-Homidan, Munirah Alqarni

Publication date: 7 April 2016

Published in: Positivity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11117-012-0180-x

zbMATH Keywords

Newton methodsemidefinite matrixcorrelation matrixalternating projections methodnearness problempositive semidefinite programing

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Semidefinite programming (90C22)

Related Items (3)

Decomposition Methods for Sparse Matrix Nearness Problems ⋮ A class of multilevel structured low-rank approximation arising in material processing ⋮ On the low rank solution of the Q‐weighted nearest correlation matrix problem

Uses Software

• NEOS

Cites Work

• Computing the nearest correlation matrix--a problem from finance
• Semidefinite programming for discrete optimization and matrix completion problems
• Euclidean distance matrices, semidefinite programming and sensor network localization
• Efficient rank reduction of correlation matrices
• Numerically stable generation of correlation matrices and their factors
• Geometry of semidefinite Max-Cut relaxations via matrix ranks
• Local minima and convergence in low-rank semidefinite programming
• Approximate and exact completion problems for Euclidean distance matrices using semidefinite programming
• An Algorithm for Restricted Least Squares Regression
• A Dual Approach to Semidefinite Least-Squares Problems
• Computational enhancements in low-rank semidefinite programming
• Functional Operators (AM-22), Volume 2

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