Fast Approximation for SVD via Gaussian Random Projections
碩士 === 國立臺灣大學 === 應用數學科學研究所 === 107 === Singular value decomposition (SVD) is a popular tool for dimension re-duction. When the size of matrix is large, the computing load is heavy. Rokhlin et al [1] proposed a randomized algorithm for fast SVD approxi-mation (abbreviated as rSVD). Often Gaussian ra...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2019
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/m9epsx |