On size-oriented long-tailed graph classification of graph neural networks

• Main Authors: LIU, Zemin, MAO, Qiheng, LIU, Chenghao, FANG, Yuan, SUN, Jianling
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Size-oriented long-tailed distribution; graph neural networks; knowledge transfer; Graphics and Human Computer Interfaces; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/7489; https://ink.library.smu.edu.sg/context/sis_research/article/8492/viewcontent/TheWebConf22_SOLT.pdf
• Institution: Singapore Management University

The prevalence of graph structures attracts a surge of investigation on graph data, enabling several downstream tasks such as multigraph classification. However, in the multi-graph setting, graphs usually follow a long-tailed distribution in terms of their sizes, i.e., the number of nodes. In partic...