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ICML
2007
IEEE
15 years 10 months ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger
MLMI
2004
Springer
15 years 3 months ago
Multistream Dynamic Bayesian Network for Meeting Segmentation
This paper investigates the automatic analysis and segmentation of meetings. A meeting is analysed in terms of individual behaviours and group interactions, in order to decompose e...
Alfred Dielmann, Steve Renals
80
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IJCAI
2001
14 years 11 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
ICML
2005
IEEE
15 years 10 months 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
BMCBI
2007
172views more  BMCBI 2007»
14 years 9 months ago
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...