Characterization of kernels in the frequency domain: A tutorial
|Titel||Characterization of kernels in the frequency domain: A tutorial|
In this presentation we look on symmetric, positive definite functions from the point of view of the frequency domain. In the machine learning community these functions are referred to as kernels. Taking a spectral approach is quite instructive. First of all, translational and rotational invariant kernels can adequately be characterized by their spectral representation, and secondly, the dual concept of a regularization operator by means of an induced Green’s function becomes more evident and handy.