About: New BFA Method Based on Attractor Neural Network and Likelihood Maximization

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: New BFA Method Based on Attractor Neural Network and Likelihood Maximization Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	What is suggested is a new approach to Boolean factor analysis, which is an extension of the previously proposed Boolean factor analysis method: Hopfield-like attractor neural network with increasing activity. We increased its applicability and robustness when complementing this method by a maximization of the learning set likelihood function defied according to the Noisy-OR generative model. We demonstrated the efficiency of the new method using the data set generated according to the model. Successful application of the method to the real data is shown when analyzing the data from the Kyoto Encyclopedia of Genes and Genomes database which contains full genome sequencing for 1368 organisms. What is suggested is a new approach to Boolean factor analysis, which is an extension of the previously proposed Boolean factor analysis method: Hopfield-like attractor neural network with increasing activity. We increased its applicability and robustness when complementing this method by a maximization of the learning set likelihood function defied according to the Noisy-OR generative model. We demonstrated the efficiency of the new method using the data set generated according to the model. Successful application of the method to the real data is shown when analyzing the data from the Kyoto Encyclopedia of Genes and Genomes database which contains full genome sequencing for 1368 organisms. (en)
Title	New BFA Method Based on Attractor Neural Network and Likelihood Maximization New BFA Method Based on Attractor Neural Network and Likelihood Maximization (en)
skos:prefLabel	New BFA Method Based on Attractor Neural Network and Likelihood Maximization New BFA Method Based on Attractor Neural Network and Likelihood Maximization (en)
skos:notation	RIV/67985807:_____/14:00398493!RIV15-AV0-67985807
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(ED1.1.00/02.0070), P(EE.2.3.20.0073)
http://linked.open...iv/cisloPeriodika	20 May
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Húsek, Dušan
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav informatiky AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	32339
http://linked.open...ai/riv/idVysledku	RIV/67985807:_____/14:00398493
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	recurrent neural network; associative memory; Hebbian learning rule; neural network application; data mining; statistics; Boolean factor analysis; information gain; dimension reduction; likelihood-maximization; bars problem (en)
http://linked.open.../riv/klicoveSlovo	bars problem neural network application dimension reduction likelihood-maximization data mining recurrent neural network statistics Boolean factor analysis associative memory information gain Hebbian learning rule
http://linked.open...odStatuVydavatele	NL - Nizozemsko
http://linked.open...ontrolniKodProRIV	[06098EB3FBA3]
http://linked.open...i/riv/nazevZdroje	Neurocomputing
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Bio-Inspired Methods: research, development and knowledge transfer IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2014
http://linked.open...v/svazekPeriodika	132
http://linked.open...iv/tvurceVysledku	Frolov, A. A. Húsek, Dušan Polyakov, P. Y. Snášel, V.
http://linked.open...ain/vavai/riv/wos	000334480500003
issn	0925-2312
number of pages	16 (xsd:int)
http://bibframe.org/vocab/doi	10.1016/j.neucom.2013.07.047

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 84 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software