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
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
Feature Interaction-aware Graph Neural Networks [pdf] [bib]
Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu and Huan Liu
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
HyperFormer: Learning Experssive Sparse Feature Representations via Hypergraph Transformer (short paper) [pdf] [code]
Kaize Ding, Albert Jiongqian Liang, Bryan Perrozi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed Chi, Huan Liu, and Derek Zhiyuan Cheng
ACM International SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
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
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
Data Augmentation for Deep Graph Learning: A Survey [pdf] [bib]
Kaize Ding, Zhe Xu, Hanghang Tong, and Huan Liu
SIGKDD Explorations, 2022
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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