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Author

Han Yu

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Sep 2026

Decoupling Semantic and Structural Alignment for Cross-Domain Federated Learning.

Cross-domain federated learning (CFL) suffers from degraded generalization due to feature discrepancies across clients. Most existing methods improve generalization by aligning cross-domain semantic features or enhancing feature diversity. However, they lack explicit constraints on the structural consistency of feature...

Wen-Jie Yao, Su-Xia Zhu, Guang-Lu Sun et al. · 0 citations
Conference Open access Sep 2026

FedEvoQ: Evolutionary Diversity Probing for Data-Quality-Aware Federated Aggregation

This work proposes a data-Quality-aware aggregation framework by introducing an Evolutionary-computation-inspired de-sign into Federated learning ( FedEvoQ), with a lightweight dual-branch architecture.

Le-Ming Wu, Yao-Chu Jin, Han Yu et al. · 0 citations

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