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FedAPE: Heterogeneous federated learning with attention-guided aggregation and prototype enhancement | Synapse
March 3, 2026
FedAPE: Heterogeneous federated learning with attention-guided aggregation and prototype enhancement
XW
Xiao Wang
Qingdao Institute of Bioenergy and Bioprocess Technology
ZW
Zhiwei Wu
Harbin Institute of Technology
JZ
Jinghua Zhu
Key Points
Improved accuracy was achieved through prototype enhancement and attention-guided aggregation methods.
An accuracy increase of 12% was noted compared to traditional federated learning approaches.
Analysis of aggregation strategies used attention to prioritize data from diverse sources.
Enhancements may offer significant benefits but further validation in real-world scenarios is necessary.
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Wang et al. (Fri,) studied this question.
synapsesocial.com/papers/69a767e1badf0bb9e87e2bd4
https://doi.org/https://doi.org/10.1016/j.future.2026.108417