In this paper an instructional framework is proposed for supporting personalised learning in the context of webbased adaptive educational hypermedia systems. A learning-focused ap...
In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, ea...
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Adaptive Hypermedia (AH) can offer a richer learning experience, tailored to students’ needs. However, authoring of AH is complex. Several models and systems have been developed...
Maurice Hendrix, Alexandra I. Cristea, Craig Stewa...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...