Preconditioner based on the Sherman-Morrison formula for regularized least squares problems

DOI10.1016/j.amc.2009.09.048zbMath1192.65036OpenAlexW2003350194MaRDI QIDQ1049312

Jun-Feng Yin

Publication date: 8 January 2010

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2009.09.048

zbMATH Keywords

numerical examplesSherman-Morrison formulaincomplete factorization methodsKrylov iterative methodssparse approximate inverse preconditionerTikhonov regularized least squares problem

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Ill-posedness and regularization problems in numerical linear algebra (65F22) Preconditioners for iterative methods (65F08)

Related Items (2)

A Tikhonov regularized penalty function approach for solving polylinear programming problems ⋮ On a generalization of Regińska's parameter choice rule and its numerical realization in large-scale multi-parameter Tikhonov regularization

Uses Software

• Regularization tools
• SparseMatrix

Cites Work

• Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems
• Restarted full orthogonalization method for shifted linear systems
• Accurate conjugate gradient methods for families of shifted systems
• The university of Florida sparse matrix collection
• Numerical Optimization
• FFT-Based Preconditioners for Toeplitz-Block Least Squares Problems
• Restarted GMRES for Shifted Linear Systems
• Preconditioning Sparse Nonsymmetric Linear Systems with the Sherman--Morrison Formula
• A robust incomplete factorization preconditioner for positive definite matrices
• Adjustment of an Inverse Matrix Corresponding to a Change in One Element of a Given Matrix
• A class of incomplete orthogonal factorization methods. I: Methods and theories
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