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Zhenzhen Xie

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#federated learning Open access Aug 2026

Structure-aware federated hypergraph continual learning

FedSHARP (Federated Structure-aware Hypergraph Anchored Representation Preservation), a structure-aware framework for federated hypergraph continual learning, is proposed and evaluated, demonstrating that preserving both node-level semantics and high-order hyperedge structures is important for federated hypergraph continual learning.

Yanxin Hu, Xiaoman Liu, Zhenzhen Xie et al. · 0 citations
Open access Jul 2026

FedAnchor: Anchored and Adaptive Federated Learning for Fault Diagnosis in Resource-Constrained Industrial IoT

FedAnchor is proposed, an anchored and adaptive FL framework for resource-heterogeneous fault diagnosis that couples resource-aware submodel allocation with structurally aligned aggregation and achieves competitive or superior accuracy compared with representative homogeneous and model-heterogeneous FL baselines.

Yanxin Hu, Xiaoman Liu, Zhenzhen Xie et al. · 0 citations

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