NDLI: Message passing for Hybrid Bayesian Networks using Gaussian mixture reduction

Content Provider	IEEE Xplore Digital Library
Author	Cheol Young Park Laskey, K.B. Costa, P.C.G. Matsumoto, S.
Copyright Year	2015
Description	Author affiliation: Sensor Fusion Lab., George Mason Univ., Fairfax, VA, USA (Cheol Young Park; Laskey, K.B.; Costa, P.C.G.; Matsumoto, S.)
Abstract	Hybrid Bayesian Networks (HBNs), which contain both discrete and continuous variables, arise naturally in many application areas (e.g., artificial intelligence, data fusion, medical diagnosis, fraud detection, etc). This paper concerns inference in an important subclass of HBNs, the conditional Gaussian (CG) networks. Inference in CG networks can be NP-hard even for special-case structures, such as poly-trees, where inference in discrete Bayesian networks can be performed in polynomial time. This paper presents an extension to the Hybrid Message Passing inference algorithm for general CG networks (i.e., networks with loops and many discrete parents). The extended algorithm uses Gaussian mixture reduction to prevent an exponential increase in the number of Gaussian mixture components. Experimental results compare performance of the new algorithm with existing algorithms.
Starting Page	210
Ending Page	216
File Size	1111925
Page Count	7
File Format	PDF
e-ISBN	9781467391528
DOI	10.1109/ICDIM.2015.7381871
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-21
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian Decision Theory Gold Artificial Intelligence Artificial neural networks Hybrid Bayesian Network Gaussian Mixture Reduction Message Passing Algorithm
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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