Building Sparse Multiple-Kernel SVM Classifiers
文献类型：期刊论文
| 作者 | Hu, Mingqing1; Chen, Yidiang1; Kwok, James Tin-Yau2 |
| 刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS
 |
| 出版日期 | 2009-05-01 |
| 卷号 | 20期号:5页码:827-839 |
| 关键词 | Gradient projection kernel methods multiple-kernel learning (MKL) sparsity support vector machine (SVM) |
| ISSN号 | 1045-9227 |
| DOI | 10.1109/TNN.2009.2014229 |
| 英文摘要 | The support vector machines (SVMs) have been very successful in many machine learning problems. However, they can be slow during testing because of the possibly large number of support vectors obtained. Recently, Wu et al. (2005) proposed a sparse formulation that restricts the SVM to use a small number of expansion vectors. In this paper, we further extend this idea by integrating with techniques from multiple-kernel learning (MKL). The kernel function in this sparse SVM formulation no longer needs to be fixed but can be automatically learned as a linear combination of kernels. Two formulations of such sparse multiple-kernel classifiers are proposed. The first one is based on a convex combination of the given base kernels, while the second one uses a convex combination of the so-called "equivalent" kernels. Empirically, the second formulation is particularly competitive. Experiments on a large number of toy and real-world data sets show that the resultant classifier is compact and accurate, and can also be easily trained by simply alternating linear program and standard SVM solver. |
| 资助项目 | National High Technology Research and Development Program of China[2007AA01Z305] ; National Natural Science Foundation of China[60775027] ; Research Grants Council of the Hong Kong Special Administrative Region, China[614907] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000265748600007 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/11794]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Hu, Mingqing |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China 2.Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong, Hong Kong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Mingqing,Chen, Yidiang,Kwok, James Tin-Yau. Building Sparse Multiple-Kernel SVM Classifiers[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS,2009,20(5):827-839. |
| APA | Hu, Mingqing,Chen, Yidiang,&Kwok, James Tin-Yau.(2009).Building Sparse Multiple-Kernel SVM Classifiers.IEEE TRANSACTIONS ON NEURAL NETWORKS,20(5),827-839. |
| MLA | Hu, Mingqing,et al."Building Sparse Multiple-Kernel SVM Classifiers".IEEE TRANSACTIONS ON NEURAL NETWORKS 20.5(2009):827-839. |
入库方式： OAI收割
来源：计算技术研究所
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