222 search results - page 13 / 45 » Geometric Neural Networks and Support Multi-Vector Machines |
103
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IJCNN
2008
IEEE
15 years 4 months ago
2008
IEEE
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
ECML
2003
Springer
15 years 2 months ago
2003
Springer
Abstract. Classical learning algorithms from the fields of artificial neural networks and machine learning, typically, do not take any costs into account or allow only costs depe...
IJCNN
2008
IEEE
15 years 4 months ago
2008
IEEE
— Effective use of support vector machines (SVMs) in classification necessitates the appropriate choice of a kernel. Designing problem specific kernels involves the definition...
IWANN
2005
Springer
15 years 3 months ago
2005
Springer
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
108
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ICANN
2005
Springer
15 years 3 months ago
2005
Springer
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...