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KDD
1995
ACM
182views Data Mining» more  KDD 1995»
15 years 4 months ago
Accelerated Quantification of Bayesian Networks with Incomplete Data
Probabilistic expert systemsbased on Bayesian networks(BNs)require initial specification both a qualitative graphical structure and quantitative assessmentof conditional probabili...
Bo Thiesson
80
Voted
NIPS
2007
15 years 2 months ago
Bayesian Agglomerative Clustering with Coalescents
We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman’s coalescent. We develop novel greedy and sequential Monte Carlo inferen...
Yee Whye Teh, Hal Daumé III, Daniel M. Roy
79
Voted
FLAIRS
2001
15 years 2 months ago
Maximal Prime Subgraph Decomposition of Bayesian Networks
A maximal prime subgraph decomposition junction tree (MPD-JT) is a useful computational structure that facilitates lazy propagation in Bayesian networks (BNs). A graphical method ...
Kristian G. Olesen, Anders L. Madsen
84
Voted
IJON
2002
98views more  IJON 2002»
15 years 10 days ago
Blind deconvolution by simple adaptive activation function neuron
The `Bussgang' algorithm is one among the most known blind deconvolution techniques in the adaptive signal processing literature. It relies on a Bayesian estimator of the sou...
Simone Fiori
JAIR
2010
119views more  JAIR 2010»
14 years 11 months ago
Active Tuples-based Scheme for Bounding Posterior Beliefs
The paper presents a scheme for computing lower and upper bounds on the posterior marginals in Bayesian networks with discrete variables. Its power lies in its ability to use any ...
Bozhena Bidyuk, Rina Dechter, Emma Rollon