Indexed Optimization: Learning Ramp-Loss SVM in Sublinear Time
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 100 === Multidimensional indexing has been frequently used for sublinear-time nearest neighbor search in various applications. In this paper, we demonstrate how this technique can be integrated into learning problem with sublinear sparsity like ramp-loss SVM. We propos...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2012
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| Online Access: | http://ndltd.ncl.edu.tw/handle/73543025733430311023 |