Integrated kernels and their properties

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摘要

Kernel machines are widely considered to be powerful tools in various fields of information science. By using a kernel, an unknown target is represented by a function that belongs to a reproducing kernel Hilbert space (RKHS) corresponding to the kernel. The application area is widened by enlarging the RKHS such that it includes a wide class of functions. In this study, we demonstrate a method to perform this by using parameter integration of a parameterized kernel. Some numerical experiments show that the unresolved problem of finding a good parameter can be neglected.

论文关键词:Kernel,Reproducing kernel Hilbert space,Projection learning,Parameter integration

论文评审过程:Received 31 October 2005, Revised 23 October 2006, Accepted 26 February 2007, Available online 7 March 2007.

论文官网地址:https://doi.org/10.1016/j.patcog.2007.02.014