Fuzzy sets complement-based gated recurrent unit
| dc.contributor.author | Ferrero Jaurrieta, Mikel | |
| dc.contributor.author | Pereira Dimuro, Graçaliz | |
| dc.contributor.author | Takáč, Zdenko | |
| dc.contributor.author | Santiago, Regivan | |
| dc.contributor.author | Fernández Fernández, Francisco Javier | |
| dc.contributor.author | Bustince Sola, Humberto | |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.contributor.funder | Gobierno de Navarra / Nafarroako Gobernua | es |
| dc.date.accessioned | 2022-03-10T07:59:59Z | |
| dc.date.available | 2022-03-10T07:59:59Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Gated Recurrent Units (GRU) are neural network gated architectures that simplify other ones (suchas, LSTM) by joining gates mainly. For this, instead of using two gates, if𝑥is the first gate, standardoperation1−𝑥is used to generate the second one, optimizing the number of parameters. In this work, we interpret this information as a fuzzy set, and we generalize the standard operation using fuzzy negations, and improving the accuracy obtained with the standard one. | en |
| dc.description.sponsorship | Grant PID2019-108392GB-I00 funded by MCIN/AEI/10.13039/501100011033 and by Tracasa Instrumental and the Immigration Policy and Justice Department of the Government of Navarre. | en |
| dc.format.extent | 9 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/42468 | |
| dc.language.iso | eng | en |
| dc.publisher | CEUR Workshop Proceedings (CEUR-WS.org) | en |
| dc.relation.ispartof | WILF’21: The 13th International Workshop on Fuzzy Logic and Applications, Dec. 20–22, 2021, Vietri sul Mare, Italy | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/ | |
| dc.rights | © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Fuzzy set complement | en |
| dc.subject | Fuzzy negations | en |
| dc.subject | Recurrent neural networks | en |
| dc.subject | Gated recurrent unit | en |
| dc.title | Fuzzy sets complement-based gated recurrent unit | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
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