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Structural Entropy-Driven Graph Diffusion Generation for One-Shot Federated Graph Learning
One-shot federated graph learning (FGL) requires the server to estimate client contributions from highly compressed information, yet conventional volume-based weighting captures the amount of client data while overlooking how its connectivity is organized. In this paper, we propose SPIRE, a Structur
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