Author

J. Gong

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#machine learning Preprint Aug 2025

SHEFL: Sparse Heterogeneous Ensemble Federated Learning with Group-Balanced Aggregation

Across four vision datasets, SHEFL improves over Fed-Ensemble (FedEns) in all data heterogeneity settings and under a matched total uplink budget, SHEFL reaches the target accuracy in fewer rounds than FedEns and improves final accuracy by up to 14.65 points.

Keumseo Ryum, J. Gong, Joonhyuk Kang · 0 citations