{"title":"Improved decomposition method for support vector machines","authors":"Weida Zhou, Li Zhang, L. Jiao","doi":"10.1109/ICCIMA.2003.1238096","DOIUrl":null,"url":null,"abstract":"An improved decomposition method for SVMs is presented. In our method, we propose a rule for selecting the working set to improve the training speed. The selection rule can be applied to any decomposition methods for SVMs. Simulation results show the feasibility and validity of our algorithm.","PeriodicalId":385362,"journal":{"name":"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIMA.2003.1238096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
An improved decomposition method for SVMs is presented. In our method, we propose a rule for selecting the working set to improve the training speed. The selection rule can be applied to any decomposition methods for SVMs. Simulation results show the feasibility and validity of our algorithm.