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JMLR
2010
140views more  JMLR 2010»
10 years 8 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
AI
2002
Springer
11 years 1 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
IPL
2008
172views more  IPL 2008»
11 years 1 months ago
Approximation algorithms for restricted Bayesian network structures
Bayesian Network structures with a maximum in-degree of k can be approximated with respect to a positive scoring metric up to an factor of 1/k. Key words: approximation algorithm,...
Valentin Ziegler
NIPS
2008
11 years 2 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
ISMIS
2005
Springer
11 years 6 months ago
Robust Inference of Bayesian Networks Using Speciated Evolution and Ensemble
Recently, there are many researchers to design Bayesian network structures using evolutionary algorithms but most of them use the only one fittest solution in the last generation. ...
Kyung-Joong Kim, Ji-Oh Yoo, Sung-Bae Cho
ITRE
2005
IEEE
11 years 7 months ago
Structure learning of Bayesian networks using a semantic genetic algorithm-based approach
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
Sachin Shetty, Min Song
CIDM
2007
IEEE
11 years 7 months ago
K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified versio...
Eli Faulkner
books