554 search results - page 34 / 111 » Variable selection using neural-network models |
UAI
1996
14 years 11 months ago
1996
We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
BMCBI
2007
14 years 9 months ago
2007
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
114
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IJCNN
2007
IEEE
15 years 4 months ago
2007
IEEE
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
77
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ICASSP
2008
IEEE
15 years 4 months ago
2008
IEEE
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
110
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BMCBI
2008
14 years 9 months ago
2008
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...