The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Given a bipartite graph of collaborative ratings, the task of recommendation and rating prediction can be modeled with graph kernels. We interpret these graph kernels as the inver...
Widespread use and general purpose computing capabilities of next generation smartphones make them the next big targets of malicious software (malware) and security attacks. Given ...
Tansu Alpcan, Christian Bauckhage, Aubrey-Derrick ...
Weighted graph regularization provides a rich framework that allows to regularize functions defined over the vertices of a weighted graph. Until now, such a framework has been only...