Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering

Detalhes bibliográficos
Autor: Díaz González, Fernando
Tipo de documento: dissertação
Data de publicação:2019
País:España
Recursos:Universidad Politécnica de Madrid
Repositório:Archivo Digital UPM
OAI Identifier:oai:oa.upm.es:64239
Acesso em linha:https://oa.upm.es/64239/
Access Level:Acceso aberto
Palavra-chave:Federated learning
Time series forecasting
Clustering
Time series feature extraction
Recurrent neural networks
Long Short-Term Memory
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oai_identifier_str oai:oa.upm.es:64239
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spelling Federated learning for time series forecasting using LSTM networks: exploiting similarities through clusteringDíaz González, FernandoFederated learningTime series forecastingClusteringTime series feature extractionRecurrent neural networksLong Short-Term MemoryBoström, HenrikGirdzijauskas, Šarūnas20192019-01-01master thesishttp://purl.org/coar/resource_type/c_bdccinfo:eu-repo/semantics/masterThesishttps://oa.upm.es/64239/reponame:Archivo Digital UPMinstname:Universidad Politécnica de MadridInglésenopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:oa.upm.es:642392026-06-21T12:45:07Z
dc.title.none.fl_str_mv Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
title Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
spellingShingle Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
Díaz González, Fernando
Federated learning
Time series forecasting
Clustering
Time series feature extraction
Recurrent neural networks
Long Short-Term Memory
title_short Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
title_full Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
title_fullStr Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
title_full_unstemmed Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
title_sort Federated learning for time series forecasting using LSTM networks: exploiting similarities through clustering
dc.creator.none.fl_str_mv Díaz González, Fernando
author Díaz González, Fernando
author_facet Díaz González, Fernando
author_role author
dc.contributor.none.fl_str_mv Boström, Henrik
Girdzijauskas, Šarūnas
dc.subject.none.fl_str_mv Federated learning
Time series forecasting
Clustering
Time series feature extraction
Recurrent neural networks
Long Short-Term Memory
topic Federated learning
Time series forecasting
Clustering
Time series feature extraction
Recurrent neural networks
Long Short-Term Memory
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://oa.upm.es/64239/
url https://oa.upm.es/64239/
dc.language.none.fl_str_mv Inglés
en
language_invalid_str_mv Inglés
en
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Archivo Digital UPM
instname:Universidad Politécnica de Madrid
instname_str Universidad Politécnica de Madrid
reponame_str Archivo Digital UPM
collection Archivo Digital UPM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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