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» On Bayesian model and variable selection using MCMC
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JMLR
2007
137views more  JMLR 2007»
14 years 9 months ago
Building Blocks for Variational Bayesian Learning of Latent Variable Models
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
Tapani Raiko, Harri Valpola, Markus Harva, Juha Ka...
76
Voted
IJAR
2006
80views more  IJAR 2006»
14 years 9 months ago
Operations for inference in continuous Bayesian networks with linear deterministic variables
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...
Barry R. Cobb, Prakash P. Shenoy
CSDA
2008
77views more  CSDA 2008»
14 years 9 months ago
Maximizing equity market sector predictability in a Bayesian time-varying parameter model
A large body of evidence has emerged in recent studies confirming that macroeconomic factors play an important role in determining investor risk premia and the ultimate path of eq...
Lorne D. Johnson, Georgios Sakoulis
ICML
2006
IEEE
15 years 10 months ago
A choice model with infinitely many latent features
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...
Carl Edward Rasmussen, Dilan Görür, Fran...
68
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IJON
2000
71views more  IJON 2000»
14 years 9 months ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli