On the Accuracy of Cross and Column Low-Rank Maxvol Approximations in Average-Reference-Cited by-同舟云学术

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On the Accuracy of Cross and Column Low-Rank Maxvol Approximations in Average

Published:2021-05 Issue:5 Volume:61 Page:786-798
ISSN:0965-5425
Container-title:Computational Mathematics and Mathematical Physics
language:en
Short-container-title:Comput. Math. and Math. Phys.

Author:

Zamarashkin N. L.,Osinsky A. I.

Publisher

Pleiades Publishing Ltd

Subject

Computational Mathematics

Link

https://link.springer.com/content/pdf/10.1134/S0965542521050171.pdf

Reference16 articles.

1. N. Halko, P. Martinsson, and J. Tropp, “Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions,” SIAM Rev. 53, 217–288 (2011).

2. A. Civril and M. Magdon-Ismail, “Column subset selection via sparse approximation of SVD,” Theor. Comput. Sci. 412, 1–14 (2012).

3. C. Boutsidis and D. P. Woodruff, “Optimal CUR matrix decompositions,” SIAM J. Comput. 46, 543–589 (2017).

4. S. A. Goreinov and E. E. Tyrtyshnikov, “The maximal-volume concept in approximation by low-rank matrices,” Contemp. Math. 268, 47–51 (2001).

5. A. I. Osinsky and N. L. Zamarashkin, “Pseudo-skeleton approximations with better accuracy estimates,” Linear Algebra Appl. 537, 221–249 (2018).

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