2 papers
cs.LG2026
Structural Entropy-Driven Graph Diffusion Generation for One-Shot Federated Graph Learning
Shutong Zheng, Lele Fu, Sheng Huang +2
One-shot federated graph learning (FGL) requires the server to estimate client contributions from highly compressed information, yet conventional volume-based weighting captures th…
cs.LG2026
Rethinking One-Shot Federated Graph Learning: Training-Free Statistical Estimation
Shutong Zheng, Sijia Chen
One-shot federated graph learning generally aims to train Graph Neural Networks (GNNs) across clients with disconnected subgraphs in a single communication round. Existing methods…