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» Training of Support Vector Machines with Mahalanobis Kernels
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ICANN
2005
Springer
13 years 11 months ago
Training of Support Vector Machines with Mahalanobis Kernels
Abstract. Radial basis function (RBF) kernels are widely used for support vector machines. But for model selection, we need to optimize the kernel parameter and the margin paramete...
Shigeo Abe
ANNPR
2006
Springer
13 years 10 months ago
Support Vector Regression Using Mahalanobis Kernels
Abstract. In our previous work we have shown that Mahalanobis kernels are useful for support vector classifiers both from generalization ability and model selection speed. In this ...
Yuya Kamada, Shigeo Abe
ICANN
2001
Springer
13 years 10 months ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
IJCNN
2006
IEEE
14 years 10 days ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
ISMIR
2005
Springer
166views Music» more  ISMIR 2005»
13 years 11 months ago
Song-Level Features and Support Vector Machines for Music Classification
Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identifica...
Michael I. Mandel, Dan Ellis