Blockchain-Enabled Asynchronous Federated Learning in Edge Computing

The fast proliferation of edge computing devices brings an increasing growth of data, which directly promotes machine learning (ML) technology development. However, privacy issues during data collection for ML tasks raise extensive concerns. To solve this issue, synchronous federated learning (FL) i...

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Detalles Bibliográficos
Autores principales: Liu, Yinghui, Qu, Youyang, Xu, Chenhao, Hao, Zhicheng, Gu, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151195/
https://www.ncbi.nlm.nih.gov/pubmed/34064942
http://dx.doi.org/10.3390/s21103335

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151195/
https://www.ncbi.nlm.nih.gov/pubmed/34064942
http://dx.doi.org/10.3390/s21103335

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