2026
Privacy-Preserving Consensus-Oriented Aggregation for Federated Learning With Heterogeneity
Achieving reliable network-wide consensus formation in distributed learning systems becomes increasingly challenging when edge nodes hold skewed data distributions. Federated learning (FL) enables privacy-preserving collaborative model training without sharing raw data, but statistical heterogeneity across nodes signif...
Xinyu Qu, Shaoyi Han, Erwu Liu et al.
· IEEE Transactions on Network... · 1 citation