Graph-Revised Convolutional Network

17 Nov 2019Donghan YuRuohong ZhangZhengbao JiangYuexin WuYiming Yang

Graph Convolutional Networks (GCNs) have received increasing attention in the machine learning community for effectively leveraging both the content features of nodes and the linkage patterns across graphs in various applications. As real-world graphs are often incomplete and noisy, treating them as ground-truth information, which is a common practice in most GCNs, unavoidably leads to sub-optimal solutions... (read more)

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