2 papers
cs.DC2026
CondenseGraph: Communication-Efficient Distributed GNN Training via On-the-Fly Graph Condensation
Zizhao Zhang, Yihan Xue, Haotian Zhu +3
Distributed Graph Neural Network (GNN) training suffers from substantial communication overhead due to the inherent neighborhood dependency in graph-structured data. This neighbor…
cs.LG2026
MetaCLBench: Meta Continual Learning Benchmark on Resource-Constrained Edge Devices
Sijia Li, Young D. Kwon, Lik-Hang Lee +1
Meta-Continual Learning (Meta-CL) enables models to learn new classes from limited labelled samples, making it promising for IoT applications where manual labelling is costly. Howe…