AGL: a Scalable System for Industrial-purpose Graph Machine Learning

16 Mar 2020 Zhang Dalong Huang Xin Liu Ziqi Hu Zhiyang Song Xianzheng Ge Zhibang Zhang Zhiqiang Wang Lin Zhou Jun Shuang Yang Qi Yuan

Machine learning over graphs have been emerging as powerful learning tools for graph data. However, it is challenging for industrial communities to leverage the techniques, such as graph neural networks (GNNs), and solve real-world problems at scale because of inherent data dependency in the graphs... (read more)

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