FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation

As the development of the Internet of Things (IoT) continues, Federated Learning (FL) is gaining popularity as a distributed machine learning framework that does not compromise the data privacy of each participant. However, the data held by enterprises and factories in the IoT often have different d...

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Detalles Bibliográficos
Autores principales: Tang, Jianwu, Ding, Xuefeng, Hu, Dasha, Guo, Bing, Shen, Yuncheng, Ma, Pan, Jiang, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385861/
https://www.ncbi.nlm.nih.gov/pubmed/37514811
http://dx.doi.org/10.3390/s23146518

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385861/
https://www.ncbi.nlm.nih.gov/pubmed/37514811
http://dx.doi.org/10.3390/s23146518

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