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» Optimizing kernel parameters by second-order methods
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ECML
2004
Springer
13 years 8 months ago
Efficient Hyperkernel Learning Using Second-Order Cone Programming
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
Ivor W. Tsang, James T. Kwok
IJCNN
2006
IEEE
13 years 10 months ago
Sparse Optimization for Second Order Kernel Methods
— We present a new optimization procedure which is particularly suited for the solution of second-order kernel methods like e.g. Kernel-PCA. Common to these methods is that there...
Roland Vollgraf, Klaus Obermayer
PPSN
2004
Springer
13 years 9 months ago
LS-CMA-ES: A Second-Order Algorithm for Covariance Matrix Adaptation
Abstract. Evolution Strategies, Evolutionary Algorithms based on Gaussian mutation and deterministic selection, are today considered the best choice as far as parameter optimizatio...
Anne Auger, Marc Schoenauer, Nicolas Vanhaecke
ESANN
2007
13 years 5 months ago
Optimizing kernel parameters by second-order methods
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...
Shigeo Abe
PR
2006
93views more  PR 2006»
13 years 4 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou