Decremental and Incremental Reshaping of Algebraic Bayesian Networks Global Structures

  • Daniel G. Levenets
  • Mikhail A. Zotov
  • Artem V. Romanov
  • Alexander L. Tulupyev
  • Andrey A. Zolotin
  • Andrey A. Filchenkov
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 451)

Abstract

The paper considers algorithms for global structures generation in algebraic Bayesian networks. A decremental algorithm for constructing a secondary structure after deleting vertex from the adjacency graph is proposed supplemented by a listing of the algorithm code and by the proof of its correctness. The results of the statistical tests for decremental algorithm are proposed graphically together with a comparative analysis of the results. Moreover, the description of incremental algorithm for adding vertex in tertiary structure is provided supplemented by a listing of the algorithm code and proof of its correctness.

Keywords

Joint graph Probabilistic graphical model Incremental algorithm Performance statistical estimate Structure learning Machine learning 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Daniel G. Levenets
    • 1
    • 2
  • Mikhail A. Zotov
    • 1
    • 2
  • Artem V. Romanov
    • 1
    • 2
  • Alexander L. Tulupyev
    • 1
    • 2
  • Andrey A. Zolotin
    • 1
    • 2
  • Andrey A. Filchenkov
    • 3
  1. 1.St. Petersburg State UniversitySaint PetersburgRussia
  2. 2.St. Petersburg Institute for Informatics and Automation of the Russian Academy of SciencesSaint PetersburgRussia
  3. 3.ITMO UniversitySaint PetersburgRussia

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