We investigate the computational complexity of the task of detecting dense regions of an unknown distribution from un-labeled samples of this distribution. We introduce a formal l...
Agent architectures have to cope with a number of internal properties (concerns), such as autonomy, learning, and mobility. As the agent complexity increases, these agent propertie...
Abstract. This work extends studies of Angluin, Lange and Zeugmann on the dependence of learning on the hypotheses space chosen for the class. In subsequent investigations, uniform...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Personalised elearning is being heralded as one of the grand challenges of next generation learning systems, in particular, its ability to support greater effectiveness, efficiency...