This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
Serious games are becoming a powerful tool in education. However, there are still open issues needing further research to generalize the use of videogames and game-like simulations...
Javier Torrente, Pablo Moreno-Ger, Baltasar Fern&a...
In this work we are investigating the learning benefits of e-Learning principles (a) within the context of a web-based intelligent tutor and (b) in the “wild,” that is, in real...
Bruce M. McLaren, Sung-Joo Lim, David Yaron, Kenne...
In this paper we study the identification of sparse interaction networks as a machine learning problem. Sparsity means that we are provided with a small data set and a high number...
Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ron...