Article Outline
Keywords
Synonyms
Introduction
Definitions
The Chain Rule for Bayesian Network
Cases/Models
Methods
Applications
See also
References
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andreassen S (1992) Knowledge representation by extended linear models. In: Keravnou E (ed) Deep Models for Medical Knowledge Engineering. Elsevier, pp 129–145
Bangsø O, Wuillemin PH (2000) Top-down Construction and Repetitive Structures Representation in Bayesian Networks, Proceedings of the Thirteenth International FLAIRS Conference. AIII Press, Cambridge, MA
Cano R, Sordo C, Gutierrez JM (2004) Applications of Bayesian Networks in Meteorology, Advances in Bayesian Networks. In: Gamez et al (eds) Springer, pp 309–327
de Dombal F, Leaper D, Staniland J, McCan A, Harrocks J (1972) Computer-aided diagnostics of acute abdominal pain. Brit Med J 2:9–13
Etxerberria R, Larrañaga P (1999) Global optimization with Bayesian networks, II Symposium on Artificial Intelligence, CIMAF-99. Special Session on Distribution and Evolutionary Optimization. ICIMAF, La Habana, Cuba, pp 332–339
Gneiting T, Raftery AE (2005) Strictly proper scoring rules, prediction, and estimation, Technical Report no. 463R. Department of Statistics, University of Washington
Heckerman D, Horvitz E, Nathwani B (1992) Towards normative expert systems: Part I, the Pathfinder project. Method Inf Med 31:90–105
Jensen FV (1996) An Introduction to Bayesian Networks. UCL Press, London
Jensen FV (1999) Gradient descent training of Bayesian networks, Proceedings of the Fifth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU). Springer, Berlin, pp 190–200
Kjærulff U (1995) HUGS: Combining exact inference and Gibbs sampling in junction trees, Proceedings of the Eleventh Conference on Artificial Intelligence. Morgan Kaufmann, San Francisco, CA, pp 368–375
Larrañaga P, Etxeberria R, Lozano JA, Peña JM (1999) Optimization by learning and simulation of Bayesian and Gaussian networks, Technical Report EHU-KZAA-IK-4/99. Department of Computer Science and Artificial Intelligence, University of the Basque Country
Lauritzen SL (1996) Graphical Models. Oxford University Press, Oxford
Livescu K, Glass J, Bilmes J (2003) Hidden feature modeling for speech recognition using dynamic Bayesian networks. Proc. EUROSPEECH, Geneva Switzerland, August–September
Mittal A, Kassim A, Tan T (2007) Bayesian Network Technologies: Applications and Graphical Models, Interface Graphics, Inc., Minneapolis, USA
Nefian AV, Liang L, Pi X, Liu X, Murphy K (2002) Dynamic Bayesian Networks for Audio-visual Speech Recognition. J Appl Signal Proc 11:1–15
Olesen KG, Lauritzen SL, Jensen FV (1992) aHUGIN: A system creating adaptive causal probabilistic networks, Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann, San Francisco, pp 223–229
Pearl J (1982) Reverend Bayes on Inference Engines: A Distributed Hierarchical Approach, National Conference on Artificial Intelligence. AAAI Press, Menlo Park, CA, pp 133–136
Pearl J (1986) Fusion, propagation, and structuring in belief networks. Artif Intell 29(3):241–288
Pearl J (1988) Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference Series in Representation and Reasoning. Morgan Kaufmann, San Francisco
Pelikan M, Goldberg DE, Cantú-Paz E (1999) BOA: The Bayesian Optimization Algorithm, Proceedings of the Genetic and Evolutionary Computation conference GECCO-99, vol 1. Morgan Kaufmann, San Francisco
Spiegelhalter DJ, Knill-Jones RP (1984) Statistical and knowledge-based approaches to clinical decision-support systems. J Royal Stat Soc A147:35–77
Spiegelhalter D, Lauritzen SL (1990) Sequential updating of conditional probabilities on directed graphical structures. Networks 20:579–605
Vomlel J (2003) Two applications of Bayesian networks, Proceedings of conference Znalosti. Ostrava, Czech Republic, pp 73–82
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag
About this entry
Cite this entry
Kammerdiner, A.R. (2008). Bayesian Networks . In: Floudas, C., Pardalos, P. (eds) Encyclopedia of Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-74759-0_32
Download citation
DOI: https://doi.org/10.1007/978-0-387-74759-0_32
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-74758-3
Online ISBN: 978-0-387-74759-0
eBook Packages: Mathematics and StatisticsReference Module Computer Science and Engineering