https://scholars.lib.ntu.edu.tw/handle/123456789/115489
標題: | Working Set Selection Using Second Order Information for Training Support Vector Machines | 作者: | Fan, Rong-En Chen, Pai-Hsuen Lin, Chih-Jen |
關鍵字: | support vector machines;decomposition methods;sequential minimal optimization;working set selection | 公開日期: | 2005 | 出版社: | 臺北市:國立臺灣大學資訊工程學系 | 起(迄)頁: | 1889-1918 | 來源出版物: | Journal of Machine Learning Research | 摘要: | Working set selection is an important step in decomposition methods for training support vector machines (SVMs). This paper develops a new technique for working set selection in SMO-type decomposition methods. It uses second order information to achieve fast con- vergence. Theoretical properties such as linear convergence are established. Experiments demonstrate that the proposed method is faster than existing selection methods using first order information. |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/20060927122855804710 | 其他識別: | 20060927122855804710 |
顯示於: | 資訊工程學系 |
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quadworkset.pdf | 430.35 kB | Adobe PDF | 檢視/開啟 |
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