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Expectation-Maximization Approach to Boolean Factor Analysis

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    SYSNO ASEP0368431
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleExpectation-Maximization Approach to Boolean Factor Analysis
    Author(s) Frolov, A. A. (RU)
    Húsek, Dušan (UIVT-O) RID, SAI, ORCID
    Polyakov, P.Y. (RU)
    Source TitleIJCNN 2011 Conference Proceedings. - Piscataway : IEEE, 2011 - ISBN 978-1-4244-9636-5
    Pagess. 559-566
    Number of pages8 s.
    ActionIJCNN 2011. International Joint Conference on Neural Networks
    Event date31.07.2011-05.08.2011
    VEvent locationSan Jose
    CountryUS - United States
    Event typeWRD
    Languageeng - English
    CountryUS - United States
    KeywordsBoolean factor analysis ; bars problem ; dendritic inhibition ; expectation-maximization ; neural network application ; statistics
    Subject RIVIN - Informatics, Computer Science
    R&D ProjectsGAP202/10/0262 GA ČR - Czech Science Foundation (CSF)
    GA205/09/1079 GA ČR - Czech Science Foundation (CSF)
    1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    CEZAV0Z10300504 - UIVT-O (2005-2011)
    UT WOS000297541200080
    EID SCOPUS80054768630
    DOI10.1109/IJCNN.2011.6033270
    AnnotationMethods for hidden structure of high-dimensional binary data discovery are one of the most important challenges facing machine learning community researchers. There are many approaches in literature that try to solve this hitherto rather ill-defined task. In the present study, we propose a most general generative model of binary data for Boolean factor analysis and introduce new Expectation-Maximization Boolean Factor Analysis algorithm which maximizes likelihood of Boolean Factor Analysis solution. Using the so-called bars problem benchmark, we compare efficiencies of Expectation-Maximization Boolean Factor Analysis algorithm with Dendritic Inhibition neural network. Then we discuss advantages and disadvantages of both approaches as regards results quality and methods efficiency.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2012
Number of the records: 1  

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