545 search results - page 43 / 109 » Support Vector Regression Using Mahalanobis Kernels |
ICANN
2007
Springer
14 years 22 days ago
2007
Springer
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
ICPR
2010
IEEE
14 years 2 months ago
2010
IEEE
In this paper, a novel approach for contour-based 2D shape recognition is proposed, using a recently introduced class of information theoretic kernels. This kind of kernels, based...
ICCV
2009
IEEE
13 years 6 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
PR
2007
13 years 8 months ago
2007
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...