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Scott, J. 
ORCID: https://orcid.org/0000-0003-2130-1091 and Tůma, M.
(2025)
Sparse linear least squares problems.
Acta Numerica, 34.
pp. 891-1010.
ISSN 1474-0508
doi: 10.1017/S0962492924000059
Abstract/Summary
Least squares problems are a cornerstone of computational science and engineering. Over the years, the size of the problems that researchers and practitioners face has constantly increased, making it essential that sparsity is exploited in the solution process. The goal of this article is to present a broad review of key algorithms for solving large-scale linear least squares problems. This includes sparse direct methods and algebraic preconditioners thatare used in combination with iterative solvers. Where software is available, this is highlighted.
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| Item Type | Article |
| URI | https://centaur.reading.ac.uk/id/eprint/118985 |
| Identification Number/DOI | 10.1017/S0962492924000059 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics |
| Publisher | Cambridge University Press |
| Download/View statistics | View download statistics for this item |
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