Publications

Selected publications in reverse-chronological order
Full publication list on Google Scholar

  1. Fangqi Zhu, Lin Zhang, Jun Gao, Bing Qin, Ruifeng Xu, Haiqin Yang ” A Diffusion Model for Event Skeleton Generation”, Annual Meeting of the Association for Computational Linguistics (ACL). 2023.

  2. Peng Xu, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqing Yang, Yujiu Yang. ”Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks”, International Conference on Machine Learning (ICML), 2023.

  3. Jiaqi Sun, Lin Zhang, Guangyi Chen, Kun Zhang, Peng Xu, Yujiu Yang. ”Feature Expansion for Graph Neural Networks”, International Conference on Machine Learning (ICML), 2023.

  4. Xinyu Zhu, Junjie Wang, Lin Zhang, Yuxiang Zhang, Ruyi Gan, Jiaxing Zhang, Yujiu Yang ”Solving Math Word Problem via Cooperative Reasoning induced Language Models”, Annual Meeting of the Association for Computational Linguistics (ACL). 2023.

  5. Lin Zhang. ”Artificial Intelligence: 70 Years Down the Road”, 2023.

  6. Yatai Ji, Junjie Wang, Yuan Gong, Lin Zhang, Yanru Zhu, Hongfa Wang, Jiaxing Zhang, Tetsuya Sakai, Yujiu Yang. ”MAP: Modality-Agnostic Uncertainty-Aware Vision-Language Pre-training Model, ” in the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

  7. Lin Zhang, and Rui Li. ”A Large-scale Friend Suggestion Architecture, ” in IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2022.

  1. Jiaqi Sun, Lin Zhang , Shenglin Zhao, Yujiu Yang. ”Improving Your Graph Neural Networks: A High-Frequency Booster, ” in IEEE International Conference on Data Mining, 2022.

  2. Junjie Wang, Yuxiang Zhang, Lin Zhang, Ping Yang, Xinyu Gao, and others. ”Fengshenbang 1.0: Being the foundation of chinese cognitive intelligence, ” 2022.

  3. Maxwell J McNeil, Lin Zhang, Petko Bogdanov. ”Temporal graph signal decomposition, ” in the Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2021.

  1. Lin Zhang,  Wenyu Zhang, Maxwell J McNeil, Nachuan Chengwang, David S. Matteson, Petko Bogdanov. ”AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series, ” The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), 2020. [code]

  2. Lin Zhang, Petko Bogdanov. ”DSL: Discriminative Subgraph Learning via Sparse Self-Representation, ” SIAM International Conference on Data Mining (SDM), 2019. [code]

  3. Lin Zhang , Alexander Gorovits, Petko Bogdanov. ”PERCeIDs: Periodic Community Detection, ” IEEE International Conference on Data Mining (ICDM), 2019. [code]