Personalized Federated Learning Algorithm with Adaptive Clustering for Non-IID IoT Data Incorporating Multi-Task Learning and Neural Network Model Characteristics

The proliferation of IoT devices has led to an unprecedented integration of machine learning techniques, raising concerns about data privacy. To address these concerns, federated learning has been introduced. However, practical implementations face challenges, including communication costs, data and...

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Detalles Bibliográficos
Autores principales: Hsu, Hua-Yang, Keoy, Kay Hooi, Chen, Jun-Ru, Chao, Han-Chieh, Lai, Chin-Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675707/
https://www.ncbi.nlm.nih.gov/pubmed/38005404
http://dx.doi.org/10.3390/s23229016

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675707/
https://www.ncbi.nlm.nih.gov/pubmed/38005404
http://dx.doi.org/10.3390/s23229016

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