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» On Bayesian model and variable selection using MCMC
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CSDA
2006
96views more  CSDA 2006»
14 years 9 months ago
Analysis of new variable selection methods for discriminant analysis
Several methods to select variables that are subsequently used in discriminant analysis are proposed and analysed. The aim is to find from among a set of m variables a smaller sub...
Joaquín A. Pacheco, Silvia Casado, Laura N&...
AAAI
2008
15 years 1 days ago
Exploiting Causal Independence Using Weighted Model Counting
Previous studies have demonstrated that encoding a Bayesian network into a SAT-CNF formula and then performing weighted model counting using a backtracking search algorithm can be...
Wei Li 0002, Pascal Poupart, Peter van Beek
PKDD
2010
Springer
162views Data Mining» more  PKDD 2010»
14 years 8 months ago
Expectation Propagation for Bayesian Multi-task Feature Selection
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
Daniel Hernández-Lobato, José Miguel...
NIPS
2003
14 years 11 months ago
On the Concentration of Expectation and Approximate Inference in Layered Networks
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
XuanLong Nguyen, Michael I. Jordan
PRL
2000
182views more  PRL 2000»
14 years 9 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen