Dual Coordinate Descent Methods for Large-scale Linear Support Vector Machines
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 97 === In many applications, data appear with a huge number of instances as well as features. Linear Support Vector Machines (SVM) is one of the most popular tools to deal with such large-scale sparse data. In this thesis, we present a novel dual coordinate descent met...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2009
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| Online Access: | http://ndltd.ncl.edu.tw/handle/07045364917408800958 |