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» On Bayesian model and variable selection using MCMC
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JMLR
2010
163views more  JMLR 2010»
14 years 4 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
15 years 2 months ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
BMCBI
2008
105views more  BMCBI 2008»
14 years 9 months ago
A Bayesian method for calculating real-time quantitative PCR calibration curves using absolute plasmid DNA standards
Background: In real-time quantitative PCR studies using absolute plasmid DNA standards, a calibration curve is developed to estimate an unknown DNA concentration. However, potenti...
Mano Sivaganesan, Shawn Seifring, Manju Varma, Ric...
ICML
2006
IEEE
15 years 10 months ago
Graph model selection using maximum likelihood
In recent years, there has been a proliferation of theoretical graph models, e.g., preferential attachment and small-world models, motivated by real-world graphs such as the Inter...
Adam Kalai, Ivona Bezáková, Rahul Sa...
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UAI
2004
14 years 11 months ago
Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
Mathias Drton, Thomas S. Richardson