Restrictively Preconditioned Conjugate Gradient Method for a Series of Constantly Augmented Least Squares Problems

DOI10.1137/19M1284853zbMath1461.65034MaRDI QIDQ5853709

Rui Li, Zeng-Qi Wang

Publication date: 11 March 2021

Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)

zbMATH Keywords

conjugate gradient methodleast squares problemsaddle point linear systemupdated preconditioning

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Preconditioners for iterative methods (65F08)

Uses Software

• LSQR
• SparseMatrix
• CRAIG

Cites Work

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• Updating preconditioners for modified least squares problems
• Multiple-Rank Modifications of a Sparse Cholesky Factorization
• The university of Florida sparse matrix collection
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• A Preconditioning Technique for Indefinite Systems Resulting from Mixed Approximations of Elliptic Problems
• An Incomplete Factorization Technique for Positive Definite Linear Systems
• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Modifying a Sparse Cholesky Factorization
• Restrictively preconditioned conjugate gradient methods for systems of linear equations
• Row Modifications of a Sparse Cholesky Factorization
• Methods of conjugate gradients for solving linear systems

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