Complexity of probabilistic inference in belief nets--an experimental study Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/tx31qn32z

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  • There are three families of exact methods used for probabilistic inference in belief nets. It is necessary to compare them and analyze the advantages and the disadvantages of each algorithm, and know the time cost of making inferences in a given belief network. This paper discusses the factors that influence the computation time of each algorithm, presents the predictive model of the time complexity for each algorithm and shows the statistical results of testing the algorithms with randomly generated belief networks.
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  • File scanned at 300 ppi (Monochrome) using Capture Perfect 3.0 on a Canon DR-9050C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
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  • description.provenance : Submitted by Kirsten Clark (kcscannerosu@gmail.com) on 2013-04-02T20:25:40Z No. of bitstreams: 1 LiZhaoyu1991.pdf: 1642633 bytes, checksum: d53a41dfcf1b912df5d4ddb6c214b1d8 (MD5)
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  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2013-04-02T20:58:52Z (GMT) No. of bitstreams: 1 LiZhaoyu1991.pdf: 1642633 bytes, checksum: d53a41dfcf1b912df5d4ddb6c214b1d8 (MD5)

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