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» Propagation Algorithms for Variational Bayesian Learning
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ICML
2009
IEEE
14 years 6 months ago
Bayesian inference for Plackett-Luce ranking models
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
John Guiver, Edward Snelson
UAI
2001
13 years 7 months ago
Expectation Propagation for approximate Bayesian inference
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
Thomas P. Minka
TIP
2011
231views more  TIP 2011»
13 years 1 days ago
Variational Bayesian Super Resolution
—In this paper, we address the super resolution (SR) problemfromasetofdegradedlowresolution(LR)imagestoobtain a high resolution (HR) image. Accurate estimation of the sub-pixel m...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
ICASSP
2011
IEEE
12 years 9 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
ICA
2004
Springer
13 years 11 months ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela