Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

KDD 2019 Wei-Lin ChiangXuanqing LiuSi SiYang LiSamy BengioCho-Jui Hsieh

Graph convolutional network (GCN) has been successfully applied to many graph-based applications; however, training a large-scale GCN remains challenging. Current SGD-based algorithms suffer from either a high computational cost that exponentially grows with number of GCN layers, or a large space requirement for keeping the entire graph and the embedding of each node in memory... (read more)

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Evaluation results from the paper

Task Dataset Model Metric name Metric value Global rank Compare
Node Classification Amazon2M Cluster-GCN F1 90.41 # 1
Node Classification PPI Cluster-GCN F1 99.36 # 2