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...
— 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...
Abstract. Evolution Strategies, Evolutionary Algorithms based on Gaussian mutation and deterministic selection, are today considered the best choice as far as parameter optimizatio...
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 ...
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...