We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
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...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
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...
Video game players often learn to map their physical actions (e.g., pressing buttons) onto their on-screen avatars' actions (e.g., wielding swords) in order to play. We explo...