We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
We introduce a novel representation for random-access rendering of antialiased vector graphics on the GPU, along with efficient encoding and rendering algorithms. The representati...
Video Compression currently is dominated by engineering and fine-tuned heuristic methods. In this paper, we propose to instead apply the well-developed machinery of machine learni...
In the context of open source development or software evolution, developers are often faced with test suites which have been developed with no apparent rationale and which may nee...
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...