We present an approach to semi-supervised learning based on an exponential family characterization. Our approach generalizes previous work on coupled priors for hybrid generative/...
Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...
Iwan de Kok, Derya Ozkan, Dirk Heylen, Louis-Phili...
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. Fuzzy-UCS combines the generalization capabilities of UCS...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
The cellular learning automaton (CLA), which is a4 combination of cellular automaton (CA) and learning automaton5 (LA), is introduced recently. This model is superior to CA because...