We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
In order to capture the full fledge semantic of complicated product data model, the expressive language ALCNHR+ K(D) is introduced. It cannot only be able to represent knowledge a...
Abstract. Functional magnetic resonance (fMRI) data are often corrupted with colored noise. To account for this type of noise, many prewhitening and pre-coloring strategies have be...
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...