Strengths and limitations of stretching for least-squares problems with some dense rows

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Persistent URL	http://purl.org/net/epubs/work/42415297
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Record Id	42415297
Title	Strengths and limitations of stretching for least-squares problems with some dense rows
Contributors	J Scott (STFC Rutherford Appleton Lab.), M Tuma
Abstract	We recently introduced a sparse stretching strategy for handling dense rows that can arise in large-scale linear least-squares problems and make such problems challenging to solve. Sparse stretching is designed to limit the amount of ﬁll within the stretched normal matrix and hence within the subsequent Cholesky factorization. While preliminary results demonstrated that sparse stretching performs signiﬁcantly better than standard stretching, it has a number of limitations. In this paper, we discuss and illustrate these limitations and propose new strategies that are designed to overcome them. Numerical experiments on problems arising from practical applications are used to demonstrate the eﬀectiveness of these new ideas. We consider both direct and preconditioned iterative solvers.
Organisation	STFC , SCI-COMP
Keywords
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Related Research Object(s):	48588574
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Language	English (EN)

Type	Details	URI(s)	Local file(s)	Year
Preprint	RAL Preprints RAL-P-2019-001, ACM Trans Math Software STFC, 2019.		RAL-P-2019-001.pdf	2019