Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Lei...
This paper suggests an evolutionary approach to design coordination strategies, a key issue in distributed intelligent systems. We focus on competitive strategies in the form of f...
We present a probabilistic model to monitor a user's emotions and engagement during the interaction with educational games. We illustrate how our probabilistic model assesses...
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
Abstract. We present a novel approach for classification using a discretised function representation which is independent of the data locations. We construct the classifier as a su...