Tutorials

  1. Toward Graph Minimally-Supervised Learning [proposal] [website]
    Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, and Huan Liu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

  2. Graph Minimally-supervised Learning [proposal] [website]
    Kaize Ding, Jundong Li, Nitesh V. Chawla, and Huan Liu
    ACM International Conference on Web Search and Data Mining (WSDM), 2022

Preprint Papers

  1. Feature Interaction-aware Graph Neural Networks [pdf] [bib]
    Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu and Huan Liu

Refereed Papers

2023

  1. Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning [pdf] [bib]
    Kaize Ding*, Yancheng Wang*, Yingzhen Yang, and Huan Liu (*equal contribution)
    AAAI Conference on Artificial Intelligence (AAAI), 2023

  2. GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection [pdf] [code]
    Yixin Liu*, Kaize Ding*, Huan Liu, and Shirui Pan (*equal contribution)
    ACM International Conference on Web Search and Data Mining (WSDM), 2023

  3. Few-shot Node Classification with Extremely Weak Supervision [pdf] [code]
    Song Wang, Yushun Dong, Kaize Ding, Chenchen, and Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2023

2022

  1. Data Augmentation for Deep Graph Learning: A Survey [pdf] [bib]
    Kaize Ding, Zhe Xu, Hanghang Tong, and Huan Liu
    SIGKDD Explorations, 2022

  2. Meta Propagation Networks for Graph Few-shot Semi-supervised Learning [pdf] [bib]
    Kaize Ding, Jianling Wang, James Caverlee and Huan Liu
    AAAI Conference on Artificial Intelligence (AAAI), 2022

  3. Cross-domain Graph Anomaly Detection [pdf] [bib]
    Kaize Ding, Kai Shu, Xuan Shan, Jundong Li and Huan Liu
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022

  4. Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification [pdf] [bib]
    Kaize Ding, Jianling Wang, Jundong Li, James Caverlee and Huan Liu
    CIKM 2022 Workshop on Trustworthy Learning on Graphs (TrustLOG), Best Paper Award

  5. Transductive Linear Probing: A Novel Framework for Few-shot Node Classification [pdf] [bib]
    Zhen Tan*, Song Wang*, Kaize Ding*, Jundong Li and Huan Liu (*equal contribution)
    Learning on Graphs Conference (LoG), 2022

  6. Generalized Few-shot Node Classification [pdf] [bib]
    Zhe Xu, Kaize Ding, Yuxiong Wang, Huan Liu and Hanghang Tong
    IEEE International Conference on Data Mining (ICDM), 2022

  7. Graph Few-shot Class-incremental Learning [pdf] [bib]
    Zhen Tan, Kaize Ding, Ruocheng Guo and Huan Liu
    ACM International Conference on Web Search and Data Mining (WSDM), 2022

  8. Few-Shot Learning on Graphs: A Survey [pdf] [bib]
    Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla and Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2022

  9. Task-Adaptive Few-shot Node Classification [pdf] [bib]
    Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen and Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

  10. Supervised Graph Contrastive Learning for Few-shot Node Classification [pdf] [bib]
    Zhen Tan, Kaize Ding, Ruocheng Guo and Huan Liu
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML-PKDD), 2022

  11. Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks [pdf] [bib]
    Ujun Jeong, Kaize Ding, Ruocheng Guo, Lu Cheng, Kai Shu and Huan Liu
    IEEE International Conference on Big Data (BigData), 2022

  12. Benchmarking Node Outlier Detection on Graphs [pdf] [bib]
    Kay Liu*, Yingtong Dou*, Yue Zhao*, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia and Philip S. Yu (*equal contribution)
    Advances in Neural Information Processing Systems (NeurIPS), 2022

  13. Causal Disentanglement with Network Information for Debiased Recommendations [pdf] [bib]
    Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selcuk Candan and Huan Liu
    International Conference on Similarity Search and Applications (SISAP), 2022

  14. Classifying COVID-19 related Meta Ads using Discourse Representation through Hypergraph [pdf] [bib]
    Ujun Jeong, Zeyad Alghamdi, Kaize Ding, Lu Cheng, Baoxin Li and Huan Liu
    International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS), 2022

2021

  1. Learning to Selectively Learn for Weakly-supervised Paraphrase Generation [pdf] [code]
    Kaize Ding, Dingcheng Li, Alexander Hanbo Li, Xing Fan, Chenlei Guo, Yang Liu and Huan Liu
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021

  2. Few-shot Network Anomaly Detection with Cross-network Meta-learning [pdf] [code]
    Kaize Ding*, Qinghai Zhou*, Hanghang Tong and Huan Liu (*equal contribution)
    The Web Conference (formerly WWW), 2021

  3. Towards Anomaly-resistant Graph Neural Networks via Reinforcement Learning (short paper) [pdf] [bib]
    Kaize Ding, Xuan Shan, and Huan Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2021

  4. Graph Neural Networks with Adaptive Frequency Response Filter [pdf] [bib]
    Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, and Jundong Li
    ACM International Conference on Information and Knowledge Management (CIKM), 2021

  5. Sequential Recommendation for Cold-start Users with Meta Transitional Learning (short paper) [pdf] [code]
    Jianling Wang, Kaize Ding and James Caverlee
    ACM International SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021

  6. Fact-enhanced Synthetic News Generation [pdf] [bib]
    Kai Shu*, Yichuan Li*, Kaize Ding and Huan Liu (*equal contribution)
    AAAI Conference on Artificial Intelligence (AAAI), 2021

  7. Session-based Recommendation with Hypergraph Attention Networks [pdf] [code]
    Jianling Wang, Kaize Ding, Ziwei Zhu and James Caverlee
    SIAM International Conference on Data Mining (SDM), 2021

  8. GLOW : Global Weighted Self-Attention Network for Web Search [pdf] [code]
    Xuan Shan, Chuanjie Liu, Yiqian Xia, Qi Chen, Yusi Zhang, Kaize Ding, Yaobo Liang, Angen Luo and Yuxiang Luo
    IEEE International Conference on Big Data (BigData), 2021

  9. FBAdTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements (demo paper) [pdf] [code]
    Ujun Jeong, Kaize Ding and Huan Liu
    International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS), 2021

2020

  1. Be More with Less: Hypergraph Attention Networks for Inductive Text Classification [pdf] [code]
    Kaize Ding, Jianling Wang, Jundong Li, Dingchneg Li, and Huan Liu
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020

  2. Graph Prototypical Networks for Few-shot Learning on Attributed Networks [pdf] [code]
    Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, and Huan Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2020

  3. Inductive Anomaly Detection on Attributed Networks [pdf] [bib]
    Kaize Ding, Jundong Li, Nitin Aagarwal and Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2020

  4. Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion [pdf] [bib]
    Jianling Wang*, Kaize Ding*, Ziwei Zhu, Yin Zhang and James Caverlee (*equal contribution)
    ACM International Conference on Web Search and Data Mining (WSDM), 2020

  5. Next-item Recommendation with Sequential Hypergraphs [pdf] [bib]
    Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu and James Caverlee
    ACM International SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020

  6. Graph Few-shot Learning with Attribute Matching [pdf] [bib]
    Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, and Qinghua Zheng
    ACM International Conference on Information and Knowledge Management (CIKM), 2020

  7. Combating Disinformation in a Social Media Age [pdf] [bib]
    Kai Shu, Amrita Bhattacharjee, Faisal Alatawi, Tahora H. Nazer, Kaize Ding, Mansooreh Karami, and Huan Liu
    WIREs Data Mining and Knowledge Discovery, 2020

  8. Challenges in Combating COVID-19 Infodemic -- Data, Tools, and Ethics [pdf] [bib]
    Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee and Huan Liu
    CIKM 2020 Workshop on Mining Actionable Insights from Social Networks (MAISoN), 2020

2019

  1. InterSpot: Interactive Spammer Detection in Social Media (demo paper) [pdf] [bib]
    Kaize Ding, Jundong Li, Shivam Dhar, Shreyash Devan, and Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2019

  2. Deep Anomaly Detection on Attributed Networks with Graph Convolutional Networks [pdf] [code]
    Kaize Ding, Jundong Li, Rohit Bhanushali, and Huan Liu
    SIAM International Conference on Data Mining (SDM), 2019

  3. Interactive Anomaly Detection on Attributed Networks [pdf] [code]
    Kaize Ding, Jundong Li, and Huan Liu
    ACM International Conference on Web Search and Data Mining (WSDM), 2019