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ICASSP
2011
IEEE

Theoretical analyses on a class of nested RKHS's

12 years 7 months ago
Theoretical analyses on a class of nested RKHS's
One of central topics of kernel machines in the field of machine learning is a model selection, especially a selection of a kernel or its parameters. In our previous work, we discussed a class of kernels forming a class of nested reproducing kernel Hilbert spaces with an invariant metric; and proved that the kernel corresponding to the smallest reproducing kernel Hilbert space, including an unknown true function, gives the optimal model. In this paper, we consider a class of kernels forming a class of nested reproducing kernel Hilbert spaces whose metrics are not always invariant and show that a similar result to the invariant case is not obtained by providing a counter example using a class of Gaussian kernels.
Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaak
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi
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