Publication: Fuzzy sets complement-based gated recurrent unit
Date
2021
Authors
Takáč, Zdenko
Santiago, Regivan
Director
Publisher
CEUR Workshop Proceedings (CEUR-WS.org)
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión publicada / Argitaratu den bertsioa
Project identifier
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/
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.
Description
Keywords
Fuzzy set complement, Fuzzy negations, Recurrent neural networks, Gated recurrent unit
Department
Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika
Faculty/School
Degree
Doctorate program
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