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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Detalhes bibliográficos

Principais autores:	Xutao Meng, Yong Li, Jianchao Lu, Xianglin Ren
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2023-11-01
coleção:	Sensors
Assuntos:	federated learning deep reinforcement learning non-IID client selection
Acesso em linha:	https://www.mdpi.com/1424-8220/23/22/9226
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