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CIKM
1997
Springer
14 years 1 days ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
14 years 15 days 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...
TSP
2010
13 years 2 months ago
Learning Gaussian tree models: analysis of error exponents and extremal structures
The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
KDD
1998
ACM
114views Data Mining» more  KDD 1998»
14 years 3 days ago
Coactive Learning for Distributed Data Mining
Weintroducecoactive learning as a distributed learning approachto data miningin networkedand distributed databases. Thecoactive learningalgorithmsact on independent data sets and ...
Dan L. Grecu, Lee A. Becker
CORR
2010
Springer
193views Education» more  CORR 2010»
13 years 6 months ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor