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IJPRAI
1998
100views more  IJPRAI 1998»
15 years 6 days ago
Obtaining The Correspondence between Bayesian and Neural Networks
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Athena Stassopoulou, Maria Petrou
ISMIS
2003
Springer
15 years 5 months ago
Comparing Hierarchical Markov Networks and Multiply Sectioned Bayesian Networks
Abstract. Multiply sectioned Bayesian networks (MSBNs) were originally proposed as a modular representation of uncertain knowledge by sectioning a large Bayesian network (BN) into ...
Cory J. Butz, H. Geng
89
Voted
FLAIRS
2004
15 years 1 months ago
Mining Bayesian Networks to Forecast Adverse Outcomes Related to Acute Coronary Syndrome
One fascinating aspect of tool building for datamining is the application of a generalized datamining tool to a specific domain. Often times, this process results in a cross disci...
Andy Novobilski, Francis M. Fesmire, David Sonnema...
JMLR
2010
140views more  JMLR 2010»
14 years 7 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
126
Voted
ICDM
2007
IEEE
153views Data Mining» more  ICDM 2007»
15 years 6 months ago
HSN-PAM: Finding Hierarchical Probabilistic Groups from Large-Scale Networks
Real-world social networks are often hierarchical, reflecting the fact that some communities are composed of a few smaller, sub-communities. This paper describes a hierarchical B...
Haizheng Zhang, Wei Li, Xuerui Wang, C. Lee Giles,...