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ICANN
2005
Springer
15 years 3 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
PRICAI
2004
Springer
15 years 3 months ago
Prediction of the Risk Types of Human Papillomaviruses by Support Vector Machines
Abstract. Infection by high-risk human papillomaviruses (HPVs) is associated with the development of cervical cancers. Classification of risk types is important to understand the ...
Je-Gun Joung, Sok June Oh, Byoung-Tak Zhang
ICPR
2002
IEEE
15 years 2 months ago
Tangent Distance Kernels for Support Vector Machines
When dealing with pattern recognition problems one encounters different types of a-priori knowledge. It is important to incorporate such knowledge into the classification method ...
Bernard Haasdonk, Daniel Keysers
NIPS
2004
14 years 11 months ago
The Entire Regularization Path for the Support Vector Machine
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
Trevor Hastie, Saharon Rosset, Robert Tibshirani, ...
NIPS
1998
14 years 11 months ago
Dynamically Adapting Kernels in Support Vector Machines
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...