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Expectation-Maximization Approach to Boolean Factor Analysis
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SYSNO ASEP 0368431 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Expectation-Maximization Approach to Boolean Factor Analysis Author(s) Frolov, A. A. (RU)
Húsek, Dušan (UIVT-O) RID, SAI, ORCID
Polyakov, P.Y. (RU)Source Title IJCNN 2011 Conference Proceedings. - Piscataway : IEEE, 2011 - ISBN 978-1-4244-9636-5 Pages s. 559-566 Number of pages 8 s. Action IJCNN 2011. International Joint Conference on Neural Networks Event date 31.07.2011-05.08.2011 VEvent location San Jose Country US - United States Event type WRD Language eng - English Country US - United States Keywords Boolean factor analysis ; bars problem ; dendritic inhibition ; expectation-maximization ; neural network application ; statistics Subject RIV IN - Informatics, Computer Science R&D Projects GAP202/10/0262 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) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000297541200080 EID SCOPUS 80054768630 DOI 10.1109/IJCNN.2011.6033270 Annotation Methods 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. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2012
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