An Optimization Method for Non-IID Federated Learning Based on Deep Reinforcement Learning

Federated learning (FL) is a distributed machine learning paradigm that enables a large number of clients to collaboratively train models without sharing data. However, when the private dataset between clients is not independent and identically distributed (non-IID), the local training objective is...

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Detalles Bibliográficos
Autores principales: Meng, Xutao, Li, Yong, Lu, Jianchao, Ren, Xianglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675381/
https://www.ncbi.nlm.nih.gov/pubmed/38005610
http://dx.doi.org/10.3390/s23229226

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675381/
https://www.ncbi.nlm.nih.gov/pubmed/38005610
http://dx.doi.org/10.3390/s23229226

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