Incomplete hyperbolic Gram-Schmidt-based preconditioners for the solution of large indefinite least squares problems

DOI10.1016/j.cam.2013.02.016zbMath1285.65018OpenAlexW2053881632MaRDI QIDQ2448357

Qiaohua Liu, Fudao Zhang

Publication date: 30 April 2014

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

Full work available at URL: https://doi.org/10.1016/j.cam.2013.02.016

zbMATH Keywords

preconditionerindefinite least squares problemsCGILSincomplete hyperbolic classical/modified Gram-Schmidt methods

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Orthogonalization in numerical linear algebra (65F25) Preconditioners for iterative methods (65F08)

Related Items (2)

Backward error and condition number analysis for the indefinite linear least squares problem ⋮ Splitting-based randomized iterative methods for solving indefinite least squares problem

Cites Work

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• A Robust Preconditioner with Low Memory Requirements for Large Sparse Least Squares Problems
• Solving the Indefinite Least Squares Problem by Hyperbolic QR Factorization
• Incomplete Methods for Solving $A^T Ax = b$
• Methods of conjugate gradients for solving linear systems
• A class of incomplete orthogonal factorization methods. I: Methods and theories

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