A comprehensive evaluation of large-scale parallel matrix factorization algorithms
碩士 === 國立交通大學 === 資訊科學與工程研究所 === 106 === Matrix factorization is an important technology in many fields. Currently, FPSG (Zhuang et al., 2013) [1] and NOMAD (Yun et al., 2014) [2] are the best parallel matrix factorization algorithms in shared-memory systems. However, we found some controversial res...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/emm74x |