a novel multiple kernel clustering method

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	a novel multiple kernel clustering method
	Zhang Lujiang ; Hu Xiaohui
	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
内容类型	会议论文
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.