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A Machine Learning Solution for Distributed Environments and Edge Computing
dc.contributor.author | Penas-Noce, Javier | |
dc.contributor.author | Fontenla-Romero, Óscar | |
dc.contributor.author | Guijarro-Berdiñas, Bertha | |
dc.date.accessioned | 2019-09-12T13:43:10Z | |
dc.date.available | 2019-09-12T13:43:10Z | |
dc.date.issued | 2019-08-09 | |
dc.identifier.citation | Penas-Noce, J.; Fontenla-Romero, Ó.; Guijarro-Berdiñas, B. A Machine Learning Solution for Distributed Environments and Edge Computing. Proceedings 2019, 21, 47. https://doi.org/10.3390/proceedings2019021047 | es_ES |
dc.identifier.issn | 2504-3900 | |
dc.identifier.uri | http://hdl.handle.net/2183/23921 | |
dc.description.abstract | [Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive and of reduced size. Moreover, they should operate in a distributed manner making use of edge computing capabilities while preserving local data privacy. The aim of this work is to provide a solution offering all these features by implementing the algorithm LANN-DSVD over a cluster of Raspberry Pi devices. In this system, every node first learns locally a one-layer neural network. Later on, they share the weights of these local networks to combine them into a global net that is finally used at every node. Results demonstrate the benefits of the proposed system. | es_ES |
dc.description.sponsorship | This research was funded by the Spanish Secretaría de Estado de Universidades e I+D+i (Grant TIN2015-65069-C2-1-R), Xunta de Galicia (Grants ED431C2018/34, ED341D R2016/045) and FEDER funds. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C2018/34 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED341D R2016/045 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2015-65069-C2-1-R/ES/ALGORITMOS ESCALABLES DE APRENDIZAJE COMPUTACIONAL: MAS ALLA DE LA CLASIFICACION Y LA REGRESION | |
dc.relation.uri | https://doi.org/10.3390/proceedings2019021047 | es_ES |
dc.rights | Atribución 4.0 Internacional (CC BY 4.0) | es_ES |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Machine learning | es_ES |
dc.subject | Distributed learning | es_ES |
dc.subject | Artificial neural networks | es_ES |
dc.subject | Big Data | es_ES |
dc.subject | Privacy-preserving | es_ES |
dc.subject | Internet of things | es_ES |
dc.subject | Edge computing | es_ES |
dc.subject | Raspberry | es_ES |
dc.subject | TensorFlow | es_ES |
dc.title | A Machine Learning Solution for Distributed Environments and Edge Computing | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Proceedings | es_ES |
UDC.volume | 21 | es_ES |
UDC.issue | 1 | es_ES |
UDC.startPage | 47 | es_ES |
dc.identifier.doi | 10.3390/proceedings2019021047 | |
UDC.conferenceTitle | 2nd XoveTIC Conference, A Coruña, Spain, 5–6 September 2019. | es_ES |