365 search results - page 30 / 73 » Generalized Chebyshev Kernels for Support Vector Classificat... |
JMLR
2006
14 years 9 months ago
2006
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
91
Voted
EMNLP
2009
14 years 7 months ago
2009
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
AVBPA
2005
Springer
15 years 3 months ago
2005
Springer
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
76
Voted
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...