String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
This paper describes a novel approach to optimal kernel placement in kernel-based tracking. If kernels are placed at arbitrary places, kernel-based methods are likely to be trappe...
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applicatio...
Abstract: Graphs are often used to describe and analyze the geometry and physicochemical composition of biomolecular structures, such as chemical compounds and protein active sites...
Thomas Fober, Marco Mernberger, Ralph Moritz, Eyke...
In this paper, we propose a novel nonparametric modeling technique, namely Space Kernel Analysis (SKA), as a result of the definition of the space kernel. We analyze the uncertai...