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Estimating a largest eigenvector by polynomial algorithms with a random start

Leyk, Z.; Wozniakowski, Henryk

In 7 and 8

the power and Lanczos algorithms with random start for estimating the largest eigenvalue of an n x n large symmetric positive definite matrix were analyzed.
In this paper we continue this study by estimating an eigenvector corresponding to the largest eigenvalue.
We analyze polynomial algorithms using Krylov information for two error criteria the randomized error and the randomized residual error.

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More About This Work

Academic Units
Computer Science
Publisher
Department of Computer Science, Columbia University
Series
Columbia University Computer Science Technical Reports, CUCS-023-96
Published Here
April 25, 2011