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Sparse approximate inverses and target matrices

Abstract:

If P has a prescribed sparsity and minimizes the Frobenius norm |I - PA||F, it is called a sparse approximate inverse of A. It is well known that the computation of such a matrix P is via the solution of independent linear least squares problems for the rows separately (and therefore in parallel). In this paper we consider the choice of other norms and introduce the idea of "target" matrices. A target matrix, T, is readily inverted and thus forms part of a preconditioner when ||T - PA|| is mi...

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Publication status:
Published

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Publisher copy:
10.1137/030601132

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
Journal:
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Volume:
26
Issue:
3
Pages:
1000-1011
Publication date:
2005-01-01
DOI:
EISSN:
1095-7197
ISSN:
1064-8275
Source identifiers:
188127
Language:
English
Keywords:
Pubs id:
pubs:188127
UUID:
uuid:12407d38-e146-4c3a-8429-728d4ea65c08
Local pid:
pubs:188127
Deposit date:
2012-12-19

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