As learning environments become increasingly available online, the fine-grained records of user activities can be captured and analyzed (generally called webmetrics) to better unde...
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
This paper presents a general learning framework for non-rigid registration of MR brain images. Given a set of training MR brain images, three major types of information are partic...