A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
As a well known fixed-point iteration algorithm for kernel
density mode-seeking, Mean-Shift has attracted wide attention
in pattern recognition field. To date, Mean-Shift algorit...
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel...
Interpolation is required in many medical image processing operations. From sampling theory, it follows that the ideal interpolation kernel is the sinc function, which is of infin...
Erik H. W. Meijering, Wiro J. Niessen, Josien P. W...