Dr Yayong Li
Postdoctoral Research Fellow
School of Mathematics and Physics
Journal Articles
Li, Yayong, Yin, Jie and Chen, Ling (2022). Informative pseudo-labeling for graph neural networks with few labels. Data Mining and Knowledge Discovery, 37 (1), 228-254. doi: 10.1007/s10618-022-00879-4
Li, Yayong, Yin, Jie and Chen, Ling (2021). SEAL: Semisupervised Adversarial Active Learning on attributed graphs. IEEE Transactions on Neural Networks and Learning Systems, 32 (7), 3136-3147. doi: 10.1109/tnnls.2020.3009682
Conference Papers
Gao, Xinyi, Chen, Tong, Zhang, Wentao, Li, Yayong, Sun, Xiangguo and Yin, Hongzhi (2024). Graph condensation for open-world graph learning. KDD '24: 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25-29 August 2024. New York, NY, United States: ACM. doi: 10.1145/3637528.3671917
Huang, Wei, Li, Yayong, Du, Weitao, Yin, Jie, Xu, Richard Yi Da, Chen, Ling and Zhang, Miao (2022). Towards deepening graph neural networks: a GNTK-based optimization perspective. International Conference on Learning Representations 2022, Virtual, 25-29 April 2022. Appleton, WI USA: International Conference on Learning Representations. doi: 10.48550/arXiv.2103.03113
Li, Yayong, Yin, Jie and Chen, Ling (2021). Unified robust training for graph neural networks against label noise. 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Virtual, 11-14 May 2021. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-75762-5_42