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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 461778.0, MPI für biologische Kybernetik / Biologische Kybernetik
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis
Authors:Kashima, H.; Oyama, S.; Yamanishi, Y.; Tsuda, K.
Editors:Theeramunkong, T.; Kijsirikul, B.; Cercone, N.; Ho, T. B.
Date of Publication (YYYY-MM-DD):2009-04
Title of Proceedings:Advances in Knowledge Discovery and Data Mining: 13th Pacific-Asia Conference PAKDD 2009
Start Page:1030
End Page:1037
Physical Description:8
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:Pairwise classification has many applications including network prediction, entity resolution, and collaborative filtering. The pairwise kernel has been proposed for those purposes by several research groups independently, and become successful in various fields. In this paper, we propose an efficient alternative which we call Cartesian kernel. While the existing pairwise kernel (which we refer to as Kronecker kernel) can be interpreted as the weighted adjacency matrix of the Kronecker product graph of two graphs, the Cartesian kernel can be interpreted as that of the Cartesian graph which is more sparse than the Kronecker product graph. Experimental results show the Cartesian kernel is much faster than the existing pairwise kernel, and at the same time, competitive with the existing pairwise kernel in predictive performance.We discuss the generalization bounds by the two pairwise kernels by using eigenvalue analysis of the kernel matrices.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:5655
URL:http://itpe.siit.tu.ac.th/pakdd2009
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