Estimating a largest eigenvector by polynomial algorithms with a random start
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.
- cucs-023-96.pdf application/pdf 195 KB Download File
- demo title for ac:110254 application/octet-stream 69.7 KB Download File
More About This Work
- Academic Units
- Computer Science
- Department of Computer Science, Columbia University
- Columbia University Computer Science Technical Reports, CUCS-023-96
- Published Here
- April 25, 2011