Name
Title | ||
|---|---|---|
Extended Lanczos bidiagonalization algorithm for low rank approximation and its applications. |
Abstract | ||
|---|---|---|
We propose an extended Lanczos bidiagonalization algorithm for finding a low rank approximation of a given matrix. We show that this method can yield better low-rank approximations than standard Lanczos bidiagonalization algorithm, without increasing the cost too much. We also describe a partial reorthogonalization process that can be used to maintain an adequate level of orthogonality of the Lanczos vectors in order to produce accurate low-rank approximations. We demonstrate the effectiveness and applicability of our algorithm for a number of applications. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.cam.2015.12.039 | J. Computational Applied Mathematics |
Keywords | Field | DocType |
Low rank approximation,Singular value decomposition,Lanczos bidiagonalization | Singular value decomposition,Mathematical optimization,Lanczos approximation,Lanczos resampling,Matrix (mathematics),Algorithm,Orthogonality,Lanczos algorithm,Low-rank approximation,Bidiagonalization,Mathematics | Journal |
Volume | Issue | ISSN |
301 | C | 0377-0427 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuansheng Wang | 1 | 0 | 0.34 |
| francois glineur | 2 | 13 | 2.36 |
| Linzhang Lu | 3 | 276 | 27.31 |
| Paul van Dooren | 4 | 649 | 90.48 |