[39] Langzhang Liang, Zenglin Xu, Zixing Song, Irwin King, and Jieping Ye. Resnorm: Tackling long-tailed degree distribution issue in graph neural networks via normalization. CoRR, abs/2206.08181, 2022.
[40] Wei Liu, Junfeng He, and Shih-Fu Chang. Large graph construction for scalable semi-supervised learning. In ICML, pages 679-686. Omnipress, 2010.
[41] Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, and Irwin King. Graph component contrastive learning for concept relatedness estimation. In AAAI, pages 13362-13370. AAAI Press, 2023.
[42] Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, and Irwin King. Graph component contrastive learning for concept relatedness estimation. Proceedings of the AAAI Conference on Artificial Intelligence, 37(11):13362-13370, Jun. 2023.
[43] Neal Parikh and Stephen Boyd. Proximal algorithms. Found. Trends Optim., 1(3):127-239, jan 2014.
[44] Michael G. Rabbat. Inferring sparse graphs from smooth signals with theoretical guarantees. In ICASSP, pages 6533-6537. IEEE, 2017.
[45] Seyed Saman Saboksayr and Gonzalo Mateos. Accelerated graph learning from smooth signals. IEEE Signal Process. Lett., 28:2192-2196, 2021.
[46] Hyunjung Shin, N. Jeremy Hill, Andreas Martin Lisewski, and Joon-Sang Park. Graph sharpening. Expert Syst. Appl., 37(12):7870-7879, 2010.
[47] Hyunjung Shin, N. Jeremy Hill, and Gunnar Ratsch. Graph based semi-supervised learning with sharper edges. In ECML, volume 4212 of Lecture Notes in Computer Science, pages 401-412. Springer, 2006.
[48] Anthony Man-Cho So. Moment inequalities for sums of random matrices and their applications in optimization. Math. Program., 130(1):125-151, 2011.
[49] Zixing Song and Irwin King. Hierarchical heterogeneous graph attention network for syntax-aware summarization. In AAAI, pages 11340-11348. AAAI Press, 2022.
[50] Zixing Song, Yueen Ma, and Irwin King. Individual fairness in dynamic financial networks. In NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022.
[51] Zixing Song, Ziqiao Meng, Yifei Zhang, and Irwin King. Semi-supervised multi-label learning for graph-structured data. In CIKM, pages 1723–1733. ACM, 2021.
[52] Zixing Song, Xiangli Yang, Zenglin Xu, and Irwin King. Graph-based semi-supervised learning: A comprehensive review. IEEE Transactions on Neural Networks and Learning Systems, pages 1-21, 2022.
[53] Zixing Song, Yifei Zhang, and Irwin King. Towards an optimal asymmetric graph structure for robust semi-supervised node classification. In KDD, pages 1656-1665. ACM, 2022.
[54] Zixing Song, Yuji Zhang, and Irwin King. Towards fair financial services for all: A temporal GNN approach for individual fairness on transaction networks. In CIKM, pages 2331-2341. ACM, 2023.
[55] Xin Sun, Tao Ge, Shuming Ma, Jingjing Li, Furu Wei, and Houfeng Wang. A unified strategy for multilingual grammatical error correction with pre-trained cross-lingual language model. In Lud De Raedt, editor, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pages 4367–4374. International Joint Conferences on Artificial Intelligence Organization, 7 2022. Main Track.
[56] Roman Vershynin. Introduction to the non-asymptotic analysis of random matrices, page 210-268. Cambridge University Press, 2012.
[57] Fei Wang and Changshui Zhang. Label propagation through linear neighborhoods. In ICML, volume 148 of ACM International Conference Proceeding Series, pages 985-992. ACM, 2006.