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» Exploiting Data Missingness in Bayesian Network Modeling
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AUSAI
2006
Springer
15 years 2 months ago
Learning Hybrid Bayesian Networks by MML
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Rodney T. O'Donnell, Lloyd Allison, Kevin B. Korb
89
Voted
CVPR
2006
IEEE
16 years 1 months ago
Unsupervised Bayesian Detection of Independent Motion in Crowds
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
Gabriel J. Brostow, Roberto Cipolla
SIAMSC
2011
219views more  SIAMSC 2011»
14 years 6 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
IJAR
2010
152views more  IJAR 2010»
14 years 9 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
INFFUS
2010
143views more  INFFUS 2010»
14 years 9 months ago
A multi-agent systems approach to distributed bayesian information fusion
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...