Neuroevolution with box mutation
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Publication Date: | 2023 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10362/157226 |
Summary: | Santos, F. J. J. B., Gonçalves, I., & Castelli, M. (2023). Neuroevolution with box mutation: An adaptive and modular framework for evolving deep neural networks. Applied Soft Computing, 147(November), 1-15. [110767]. https://doi.org/10.1016/j.asoc.2023.110767 --- Funding: This work is funded by national funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the projects CISUC - UID/CEC/00326/2020, UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS, and by European Social Fund, through the Regional Operational Program Centro 2020 . |
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Neuroevolution with box mutationAn adaptive and modular framework for evolving deep neural networksNeuroevolutionEvolutionary deep learningNeural architecture searchSupervised learningSoftwareSantos, F. J. J. B., Gonçalves, I., & Castelli, M. (2023). Neuroevolution with box mutation: An adaptive and modular framework for evolving deep neural networks. Applied Soft Computing, 147(November), 1-15. [110767]. https://doi.org/10.1016/j.asoc.2023.110767 --- Funding: This work is funded by national funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the projects CISUC - UID/CEC/00326/2020, UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS, and by European Social Fund, through the Regional Operational Program Centro 2020 .The pursuit of self-evolving neural networks has driven the emerging field of Evolutionary Deep Learning, which combines the strengths of Deep Learning and Evolutionary Computation. This work presents a novel method for evolving deep neural networks by adapting the principles of Geometric Semantic Genetic Programming, a subfield of Genetic Programming, and Semantic Learning Machine. Our approach integrates evolution seamlessly through natural selection with the optimization power of backpropagation in deep learning, enabling the incremental growth of neural networks’ neurons across generations. By evolving neural networks that achieve nearly 89% accuracy on the CIFAR-10 dataset with relatively few parameters, our method demonstrates remarkable efficiency, evolving in GPU minutes compared to the field standard of GPU days.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNSantos, Frederico J. J. B.Gonçalves, IvoCastelli, Mauro2023-09-01T22:16:01Z2023-11-012023-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article15application/pdfhttp://hdl.handle.net/10362/157226eng1568-4946PURE: 70324693https://doi.org/10.1016/j.asoc.2023.110767info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:14:00Zoai:run.unl.pt:10362/157226Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:44:22.120701Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Neuroevolution with box mutation An adaptive and modular framework for evolving deep neural networks |
title |
Neuroevolution with box mutation |
spellingShingle |
Neuroevolution with box mutation Santos, Frederico J. J. B. Neuroevolution Evolutionary deep learning Neural architecture search Supervised learning Software |
title_short |
Neuroevolution with box mutation |
title_full |
Neuroevolution with box mutation |
title_fullStr |
Neuroevolution with box mutation |
title_full_unstemmed |
Neuroevolution with box mutation |
title_sort |
Neuroevolution with box mutation |
author |
Santos, Frederico J. J. B. |
author_facet |
Santos, Frederico J. J. B. Gonçalves, Ivo Castelli, Mauro |
author_role |
author |
author2 |
Gonçalves, Ivo Castelli, Mauro |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) Information Management Research Center (MagIC) - NOVA Information Management School RUN |
dc.contributor.author.fl_str_mv |
Santos, Frederico J. J. B. Gonçalves, Ivo Castelli, Mauro |
dc.subject.por.fl_str_mv |
Neuroevolution Evolutionary deep learning Neural architecture search Supervised learning Software |
topic |
Neuroevolution Evolutionary deep learning Neural architecture search Supervised learning Software |
description |
Santos, F. J. J. B., Gonçalves, I., & Castelli, M. (2023). Neuroevolution with box mutation: An adaptive and modular framework for evolving deep neural networks. Applied Soft Computing, 147(November), 1-15. [110767]. https://doi.org/10.1016/j.asoc.2023.110767 --- Funding: This work is funded by national funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the projects CISUC - UID/CEC/00326/2020, UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS, and by European Social Fund, through the Regional Operational Program Centro 2020 . |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-09-01T22:16:01Z 2023-11-01 2023-11-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://hdl.handle.net/10362/157226 |
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http://hdl.handle.net/10362/157226 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1568-4946 PURE: 70324693 https://doi.org/10.1016/j.asoc.2023.110767 |
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openAccess |
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15 application/pdf |
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