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Keao Xi

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Book Open access Aug 2026

Disagreement-Aware Subgraph Federated Learning via Uncertainty-Guided Local-Global Alignment

FedDUA is proposed, a novel disagreement-aware and uncertainty-guided framework for subgraph FL that first models cross-client semantic disagreement via a lightweight semantic anchor graph and derives adaptive aggregation weights for reliable global federated knowledge.

Keao Xi, Nan-Nan Wu, Yi-Ming Zhao et al. · 0 citations
Book Open access Aug 2026

Disagreement-Aware Subgraph Federated Learning via Uncertainty-Guided Local-Global Alignment

Subgraph federated learning (subgraph FL) enables collaborative graph neural network training without sharing raw graph data, but suffers from severe Non-IID distributions and structural fragmentation. In such settings, Non-IID distributions induce pronounced client specialization, where each client excels in a subset...

Keao Xi, Nannan Wu, Yiming Zhao et al. · 0 citations

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