FedTP: Federated Learning by Transformer Personalization

Federated learning is an emerging learning paradigm where multiple clients collaboratively train a machine learning model in a privacy-preserving manner. Personalized federated learning extends this paradigm to overcome heterogeneity across clients by learning personalized models. Recently, there ha...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2024-10, Vol.35 (10), p.13426-13440
Hauptverfasser:	Li, Hongxia, Cai, Zhongyi, Wang, Jingya, Tang, Jiangnan, Ding, Weiping, Lin, Chin-Teng, Shi, Ye
Format:	Artikel
Sprache:	eng
Schlagworte:	Data models Federated learning Hypernetworks learn-to-personalize personalized federated learning Scalability self-attention Servers Task analysis Training transformer Transformers
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