Special Section on Iterative Methods in Numerical Linear Algebra

1994 ◽  
Vol 15 (2) ◽  
pp. 295-296 ◽  
Author(s):  
Tom Manteuffel ◽  
Steve McCormick
1994 ◽  
Vol 15 (3) ◽  
pp. 545-546
Author(s):  
Tom Manteuffel ◽  
Steve McCormick

1992 ◽  
Vol 13 (1) ◽  
pp. vii-viii
Author(s):  
Thomas A. Manteuffel ◽  
Linda R. Petzold

Author(s):  
Stefano Massei

AbstractVarious applications in numerical linear algebra and computer science are related to selecting the $$r\times r$$ r × r submatrix of maximum volume contained in a given matrix $$A\in \mathbb R^{n\times n}$$ A ∈ R n × n . We propose a new greedy algorithm of cost $$\mathcal O(n)$$ O ( n ) , for the case A symmetric positive semidefinite (SPSD) and we discuss its extension to related optimization problems such as the maximum ratio of volumes. In the second part of the paper we prove that any SPSD matrix admits a cross approximation built on a principal submatrix whose approximation error is bounded by $$(r+1)$$ ( r + 1 ) times the error of the best rank r approximation in the nuclear norm. In the spirit of recent work by Cortinovis and Kressner we derive some deterministic algorithms, which are capable to retrieve a quasi optimal cross approximation with cost $$\mathcal O(n^3)$$ O ( n 3 ) .


Author(s):  
Nicola Mastronardi ◽  
Gene H Golub ◽  
Shivkumar Chandrasekaran ◽  
Marc Moonen ◽  
Paul Van Dooren ◽  
...  

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