Publications & Work in Submission
Published 7 papers in top AI conferences, 3 as first author, 2 as co-first author, 800+ citations.
Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu. “Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs.” In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ‘21). 2021. [KDD-21] [PDF] [CODE]
Han Liu, Xiaotong Zhang, Xianchao Zhang, Qimai Li, Xiao-Ming Wu. “RPC: Representative possible world based consistent clustering algorithm for uncertain dat”, Computer Communications, Volume 176, 2021, Pages 128-137, ISSN 0140-3664.
Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-lai Chung. “A Closer Look at the Training Strategy for Modern Meta-Learning.” in Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS-20).
Guangfeng Yan, Lu Fan, Qimai Li (co-first author), Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y.S. Lam. “Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification.” In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (Long Paper). 2020. [ACL-20] [PDF] [CODE]
Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y.S. Lam. “Reconstructing Capsule Networks for Zero-shot Intent Classification.” In Proceedings of 2019 Conference on Empirical Methods in Natural Language Processing (Long Paper). 2019. [EMNLP-19] [PDF]
Xiaotong Zhang, Han Liu, Qimai Li (co-first author) and Xiao-Ming Wu. “Attributed Graph Clustering via Adaptive Graph Convolution.” In Proceedings of the 28th International Joint Conference on Artificial Intelligence. 2019. [IJCAI-19] [PDF] [CODE] [PPT]
Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, and Zhichao Guan. “Label Efficient Semi-Supervised Learning via Graph Filtering.” In IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019. [CVPR-19] [PDF] [CODE] [PPT] [POSTER]
Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, and Victor OK Li. “Large Margin Meta-Learning for Few-Shot Classification.” Workshop on Meta-Learning (MetaLearn 2018) at NeurIPS. 2018.
Qimai Li, Zhichao Han, and Xiao-Ming Wu. “Deeper insights into graph convolutional networks for semi-supervised learning.” Thirty-Second AAAI Conference on Artificial Intelligence. 2018. Selected as one of the Most Influential AAAI Papers by Paper Digest (673 Citations as of June 29, 2021). [AAAI-18 Oral] [PDF] [CODE] [BLOG] [PPT]