IEEE

When Sparse Graph Representation Learning Falls into Domain Shift: Feature Augmentation for Cross-Domain Graph Meta-Learning

Abstract: Graph Meta-learning methods have improved the performance of few-shot node classification by means of applying meta-learning to the data in non-Euclidean domains. However, most works focus ...
IEEE

VFGCN: A Vertical Federated Learning Framework With Privacy Preserving for Graph Convolutional Network

Abstract: Due to the robust representational capabilities of graph data, employing graph neural networks for its processing has demonstrated superior performance over conventional deep learning ...