Ordinal classification is a form of multi-class classification where there is an inherent ordering between the classes, but not a meaningful numeric difference between them. Althou...
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
This paper presents the design principles, development and implementation of an e-learning framework, called Intelligent Cognitive Agents (InCA). The InCA framework is an ontology...
Liana Razmerita, Thierry Nabeth, Albert A. Angehrn...
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...