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AI
2002
Springer
14 years 11 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 ...
CIKM
1997
Springer
15 years 3 months 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
CORR
2008
Springer
79views Education» more  CORR 2008»
14 years 12 months ago
A System Theoretic Approach to Bandwidth Estimation
It is shown that bandwidth estimation in packet networks can be viewed in terms of min-plus linear system theory. The available bandwidth of a link or complete path is expressed i...
Jörg Liebeherr, Markus Fidler, Shahrokh Valae...
UAI
1996
15 years 1 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
ICML
2005
IEEE
16 years 17 days ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes