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DAWAK
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. This paper addresses a task of variable selection which consists in choosing a subset of variables that is sufficient to predict the target label well. Here instead of tr...
BMCBI
2007
13 years 4 months ago
2007
Background: A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk asse...
AAAI
2011
12 years 4 months ago
2011
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
JMLR
2007
13 years 4 months ago
2007
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...