1235 search results - page 33 / 247 » Learning with Idealized Kernels |
PKDD
2009
Springer
15 years 6 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...
114
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NIPS
2008
15 years 1 months ago
2008
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
121
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JMLR
2006
14 years 11 months ago
2006
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
130
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GFKL
2007
Springer
15 years 3 months ago
2007
Springer
Kernel methods offer a flexible toolbox for pattern analysis and machine learning. A general class of kernel functions which incorporates known pattern invariances are invariant d...
ICML
2003
IEEE
16 years 20 days ago
2003
IEEE
In various application domains, including image recognition, it is natural to represent each example as a set of vectors. With a base kernel we can implicitly map these vectors to...