In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
The purpose of this research is to develop a webbased learning environment where teachers can provide subject content using SCORM Simple Sequence Specification (SSS) mechanism wit...
The involvement of technology to support and enhance learning is ever increasing; for example moving from the traditional blackboard to electronic whiteboards, from printed books ...
Willem-Paul Brinkman, Charles van der Mast, Annett...