We develop a framework based on Bayesian model averaging to explain how animals cope with uncertainty about contingencies in classical conditioning experiments. Traditional accoun...
Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. ...
Various design and model selection methods are available for supersaturated designs having more factors than runs but little research is available on their comparison and evaluati...
Recognition difficulty is statistically linked to ??? subject covariate factors such as age and gender for three face recognition algorithms: principle components analysis, an int...
Geof H. Givens, J. Ross Beveridge, Bruce A. Draper...
—We propose a general synchronous model of lattice random fields which could be used similarly to Gibbs distributions in a Bayesian framework for image analysis, leading to algor...
A class of sparse regularization functions are considered for the developing sparse classifiers for determining facial gender. The sparse classification method aims to both select...