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» Bayesian learning of measurement and structural models
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BIOCOMP
2006
15 years 1 months ago
Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
ICMCS
2008
IEEE
207views Multimedia» more  ICMCS 2008»
15 years 6 months ago
Structure learning in a Bayesian network-based video indexing framework
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Siwar Baghdadi, Guillaume Gravier, Claire-Hé...
GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
15 years 4 months ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
ADMA
2006
Springer
121views Data Mining» more  ADMA 2006»
15 years 5 months ago
A New Polynomial Time Algorithm for Bayesian Network Structure Learning
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Sanghack Lee, Jihoon Yang, Sungyong Park
ICML
2009
IEEE
16 years 21 days ago
Learning from measurements in exponential families
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
Percy Liang, Michael I. Jordan, Dan Klein