Abstract. We develop a probabilistic interpretation of non-linear component extraction in neural networks that activate their hidden units according to a softmaxlike mechanism. On ...
A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and hel...
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
We consider the problem of modeling the content structure of texts within a specific domain, in terms of the topics the texts address and the order in which these topics appear. W...