a novel multiple kernel clustering method
文献类型：会议论文
| 作者 | Zhang Lujiang ; Hu Xiaohui |
| 出版日期 | 2012 |
| 会议名称 | 8th International Conference on Emerging Intelligent Computing Technology and Applications, ICIC 2012 |
| 会议日期 | July 25, 2012 - July 29, 2012 |
| 会议地点 | Huangshan, China |
| 关键词 | Intelligent computing |
| 页码 | 87-92 |
| 中文摘要 | Recently Multiple Kernel Learning (MKL) has gained increasing attention in constructing a combinational kernel from a number of basis kernels. In this paper, we proposed a novel approach of multiple kernel learning for clustering based on the kernel k-means algorithm. Rather than using a convex combination of multiple kernels over the whole input space, our method associates to each cluster a localized kernel. We assign to each cluster a weight vector for feature selection and combine it with a Gaussian kernel to form a unique kernel for the corresponding cluster. A locally adaptive strategy is used to localize the kernel for each cluster with the aim of minimizing the within-cluster variance of the corresponding cluster. We experimentally compared our methods to kernel k-means and spectral clustering on several data sets. Empirical results demonstrate the effectiveness of our method. © 2012 Springer-Verlag. |
| 英文摘要 | Recently Multiple Kernel Learning (MKL) has gained increasing attention in constructing a combinational kernel from a number of basis kernels. In this paper, we proposed a novel approach of multiple kernel learning for clustering based on the kernel k-means algorithm. Rather than using a convex combination of multiple kernels over the whole input space, our method associates to each cluster a localized kernel. We assign to each cluster a weight vector for feature selection and combine it with a Gaussian kernel to form a unique kernel for the corresponding cluster. A locally adaptive strategy is used to localize the kernel for each cluster with the aim of minimizing the within-cluster variance of the corresponding cluster. We experimentally compared our methods to kernel k-means and spectral clustering on several data sets. Empirical results demonstrate the effectiveness of our method. © 2012 Springer-Verlag. |
| 收录类别 | EI |
| 会议主办者 | IEEE Computational Intelligence Society; International Neural Network Society; National Science Foundation of China |
| 会议录 | Communications in Computer and Information Science
 |
| 语种 | 英语 |
| ISSN号 | 1865-0929 |
| ISBN号 | 9783642318368 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15801]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Zhang Lujiang,Hu Xiaohui. a novel multiple kernel clustering method[C]. 见:8th International Conference on Emerging Intelligent Computing Technology and Applications, ICIC 2012. Huangshan, China. July 25, 2012 - July 29, 2012. |
入库方式： OAI收割
来源：软件研究所
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