A per-step layer-wise embedding exchange in federated GNNs recovers centralized node representations for cross-client subgraph patterns under an extended-subgraph assumption.
arXiv preprint arXiv:2401.04336 , year =
2 Pith papers cite this work. Polarity classification is still indexing.
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PRISM proposes a topology-aware cross-modal imputation framework for client-level modality-deficient multimodal federated graph learning that improves deficient clients by 4.48% on average over baselines across six datasets.
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Federated Cross-Client Subgraph Pattern Detection
A per-step layer-wise embedding exchange in federated GNNs recovers centralized node representations for cross-client subgraph patterns under an extended-subgraph assumption.
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PRISM: Topology-Aware Cross-Modal Imputation for Modality-Deficient Federated Graph Learning
PRISM proposes a topology-aware cross-modal imputation framework for client-level modality-deficient multimodal federated graph learning that improves deficient clients by 4.48% on average over baselines across six datasets.