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» Dynamically Adapting Kernels in Support Vector Machines
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IJCNN
2000
IEEE
13 years 10 months ago
A Neural Support Vector Network Architecture with Adaptive Kernels
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
Pascal Vincent, Yoshua Bengio
SIGIR
2003
ACM
13 years 11 months ago
Question classification using support vector machines
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
Dell Zhang, Wee Sun Lee
ICANN
2001
Springer
13 years 10 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
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
ICPR
2008
IEEE
14 years 5 days ago
Fast model selection for MaxMinOver-based training of support vector machines
OneClassMaxMinOver (OMMO) is a simple incremental algorithm for one-class support vector classification. We propose several enhancements and heuristics for improving model select...
Fabian Timm, Sascha Klement, Thomas Martinetz