3 accepted papers
Kernel regression problem with autocorrelation prior is discussed in this paper. We revealed the optimal model of the kernel ridge regression in terms of the expected generalization error under the assumed autocorrelation prior. This result agrees with the optimal model of the Gaussian process regre…
The kernel-induced sampling theorem enables us to determine whether the sampling theorem holds or not for a reproducing kernel Hilbert space and a given set of sampling points. However, it is not easy to specifically calculate the necessary and sufficient condition formula except in some special cas…
Theoretical validity of empirical error minimization in multiple kernel regressors is discussed in this paper. Generalization error of a kernel machine is usually evaluated by the induced norm of the difference between an unknown true function and an estimated one in an appropriate reproducing kerne…