Highly Scalable Parallelism of Integrated Randomized Singular Value Decomposition with Big Data Applications
碩士 === 國立臺灣大學 === 應用數學科學研究所 === 105 === Low-rank approximation plays an important role in big data analysis. Integrated Singular Value Decomposition (iSVD) is an algorithm for computing low-rank approximate singular value decomposition of large size matrices. The iSVD integrates different low-rank S...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2017
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| Online Access: | http://ndltd.ncl.edu.tw/handle/bvks4s |