We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
Two sets of multimedia learning materials were compared for their ability to promote learning of introductory computer programming The first set of materials was a sequentially na...
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
We study the problem of automatically discovering semantic associations between schema elements, namely foreign keys. This problem is important in all applications where data sets...
Alexandra Rostin, Oliver Albrecht, Jana Bauckmann,...
The vast amount of information freely available on the Web constitutes a unparalleled resource for the automatic knoweledge discovery and learning. In this paper we propose a study...