Abstract: One of the difficulties that self-directed learners face on their learning process is choosing the right learning resources. One of the goals of adaptive educational syst...
Abstract: The problem of modeling and assessing an individual’s ability level is central to learning environments. Numerous approaches exists to this end. Computer Adaptive Testi...
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Background: Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statist...
Mirko Francesconi, Daniel Remondini, Nicola Nerett...