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Two Expectation-Maximization Algorithms for Boolean Factor Analysis
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SYSNO ASEP 0369641 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Two Expectation-Maximization Algorithms for Boolean Factor Analysis Překlad názvu Dva EM algoritmy pro Booleovskou faktorovou analýzu Tvůrce(i) Frolov, A. A. (RU)
Húsek, Dušan (UIVT-O) RID, SAI, ORCID
Polyakov, P.Y. (RU)Zdroj.dok. Neurocomputing. - : Elsevier - ISSN 0925-2312
Roč. 130, 23 April (2014), s. 83-97Poč.str. 15 s. Jazyk dok. eng - angličtina Země vyd. NL - Nizozemsko Klíč. slova Boolean Factor analysis ; Binary Matrix factorization ; Neural networks ; Binary data model ; Dimension reduction ; Bars problem Vědní obor RIV IN - Informatika CEP GAP202/10/0262 GA ČR - Grantová agentura ČR CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000333233200012 EID SCOPUS 84893735667 DOI 10.1016/j.neucom.2012.02.055 Anotace Methods for the discovery of hidden structures of high-dimensional binary data are one of the most important challenges facing the community of machine learning researchers. There are many approaches in the literature that try to solve this hitherto rather ill-defined task. In the present, we propose a general generative model of binary data for Boolean Factor Analysis and introduce two new Expectation-Maximization Boolean Factor Analysis algorithms which maximize the likelihood of a Boolean Factor Analysis solution. To show the maturity of our solutions we propose an informational measure of Boolean Factor Analysis efficiency. Using the so-called bars problem benchmark, we compare the efficiencies of the proposed algorithms to that of Dendritic Inhibition Neural Network, Maximal Causes Analysis, and Boolean Matrix Factorization. Last mentioned methods were taken as related methods as they are supposed to be the most efficient in bars problem benchmark. Then we discuss the peculiarities of the two methods we proposed and the three related methods in performing Boolean Factor Analysis. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2015
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