Graph Augmentation Learning

Author:

Yu Shuo1,Huang Huafei1,Dao Minh N.2,Xia Feng2

Affiliation:

1. School of Software, Dalian University of Technology, China

2. School of Engineering, IT and Physical Sciences, Federation University Australia, Australia

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

ACM

Reference68 articles.

1. Tianle Cai , Shengjie Luo , Keyulu Xu , Di He , Tie-Yan Liu , and Liwei Wang . 2021 . GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training . In Proceedings of International Conference on Machine Learning, Vol. 139 . 1204–1215. Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, and Liwei Wang. 2021. GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. In Proceedings of International Conference on Machine Learning, Vol. 139. 1204–1215.

2. Chen Cao , Shihao Li , Shuo Yu , and Zhikui Chen . 2021 . Fake Reviewer Group Detection in Online Review Systems. In International Conference on Data Mining Workshops. IEEE, 935–942 . Chen Cao, Shihao Li, Shuo Yu, and Zhikui Chen. 2021. Fake Reviewer Group Detection in Online Review Systems. In International Conference on Data Mining Workshops. IEEE, 935–942.

3. Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View

4. Ming Chen , Zhewei Wei , Zengfeng Huang , Bolin Ding , and Yaliang Li . 2020 . Simple and deep graph convolutional networks . In Proceedings of International Conference on Machine Learning, Vol. 119 . 1725–1735. Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, and Yaliang Li. 2020. Simple and deep graph convolutional networks. In Proceedings of International Conference on Machine Learning, Vol. 119. 1725–1735.

5. Learning on Attribute-Missing Graphs

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