Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
We present a nonparametric Bayesian model for multi-task learning, with a focus on feature selection in binary classification. The model jointly identifies groups of similar tas...
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...
One of the central problems in cognitive science is determining the mental representations that underlie human inferences. Solutions to this problem often rely on the analysis of ...
Elimination by aspects (EBA) is a probabilistic choice model describing how humans decide between several options. The options from which the choice is made are characterized by b...