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ICML
2009
IEEE
14 years 9 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
CDC
2009
IEEE
167views Control Systems» more  CDC 2009»
14 years 1 months ago
Factoring Dynamic Bayesian Networks based on structural observability
— Dynamic Bayesian Networks (DBNs) provide a systematic framework for robust online monitoring of dynamic systems. This paper presents an approach for increasing the efficiency ...
Indranil Roychoudhury, Gautam Biswas, Xenofon D. K...
ICML
2006
IEEE
14 years 9 months ago
Bayesian learning of measurement and structural models
We present a Bayesian search algorithm for learning the structure of latent variable models of continuous variables. We stress the importance of applying search operators designed...
Ricardo Silva, Richard Scheines
ECSQARU
1995
Springer
14 years 4 days ago
Parametric Structure of Probabilities in Bayesian Networks
The paper presents a method for uncertainty propagation in Bayesian networks in symbolic, as opposed to numeric, form. The algebraic structure of probabilities is characterized. Th...
Enrique Castillo, José Manuel Gutiér...
IJAR
2006
89views more  IJAR 2006»
13 years 8 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander