2 papers
cs.LG2024
Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck
Xingcheng Fu, Yisen Gao, Beining Yang +4
Dataset condensation has significantly improved model training efficiency, but its application on devices with different computing power brings new requirements for different data…
cs.LG2024
FedRGL: Robust Federated Graph Learning for Label Noise
De Li, Haodong Qian, Qiyu Li +4
Federated Graph Learning (FGL) is a distributed machine learning paradigm based on graph neural networks, enabling secure and collaborative modeling of local graph data among clien…