Jundong Li
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Publications

More information can be found in my Google Scholar and DBLP profiles.
* indicates equal contribution.

Preprint

  1. A Benchmark for Fairness-Aware Graph Learning, arXiv:2407.12112.
    Yushun Dong, Song Wang, Zhenyu Lei, Zaiyi Zheng, Jing Ma, Chen Chen, Jundong Li

  2. CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models, arXiv:2407.02408.
    Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li

  3. Cognitively Inspired Energy-Based World Models, arXiv:2406.08862.
    Alexi Gladstone, Ganesh Nanduru, Md Mofijul Islam, Aman Chadha, Jundong Li, Tariq Iqbal

  4. Spectral Greedy Coresets for Graph Neural Networks, arXiv:2405.17404.
    Mucong Ding, Yinhan He, Jundong Li, Furong Huang

  5. Safety in Graph Machine Learning: Threats and Safeguards, arXiv:2405.11034.
    Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li

  6. Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era, 2403.08946.
    Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu

  7. GraphRCG: Self-conditioned Graph Generation via Bootstrapped Representations, 2403.01071.
    Song Wang, Zhen Tan, Xinyu Zhao, Tianlong Chen, Huan Liu, Jundong Li

  8. ELEGANT: Certified Defense on the Fairness of Graph Neural Networks, arXiv:2311.02757.
    Yushun Dong, Binchi Zhang, Hanghang Tong, Jundong Li

2025

  1. Demystify Epidemic Containment in Directed Networks: Theory and Algorithms
    Yinhan He, Chen Chen, Song Wang, Guanghui Min, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2025. (acceptance rate: 106/606=17.5%)

  2. Invariant Shape Representation Learning For Image Classification
    Tonmoy Hossain, Jing Ma, Jundong Li, Miaomiao Zhang
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.

2024

  1. Mixture of Demonstrations for In-Context Learning
    Song Wang, Zihan Chen, Chengshuai Shi, Cong Shen, Jundong Li
    Neural Information Processing Systems (NeurIPS), 2024. (acceptance rate: 25.8%).

  2. Efficient Prompt Optimization Through the Lens of Best Arm Identification
    Chengshuai Shi, Kun Yang, Zihan Chen, Jundong Li, Jing Yang, Cong Shen
    Neural Information Processing Systems (NeurIPS), 2024. (acceptance rate: 25.8%).

  3. KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models
    Zaiyi Zheng, Yushun Dong, Song Wang, Haochen Liu, Qi Wang, Jundong Li
    IEEE International Conference on Big Data (IEEE BigData), 2024.

  4. Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective on Molecule Graphs
    Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li
    Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), 2024.

  5. "Glue Pizza and Eat Rocks" - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models
    Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.

  6. Large Language Models for Data Annotation: A Survey
    Zhen Tan, Dawei Li, Song Wang, Alimohammad Beigi, Bohan Jiang, Amrita Bhattacharjee, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.

  7. Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
    Song Wang, Xiaodong Yang, Rashidul Islam, Huiyuan Chen, Minghua Xu, Jundong Li, Yiwei Cai
    IEEE International Conference on Data Mining (ICDM), 2024.

  8. Understanding and Modeling Job Marketplace with Pretrained Language Models
    Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li
    ACM International Conference on Information and Knowledge Management (CIKM), 2024. (Applied Research Track)

  9. Federated Graph Learning with Structure Proxy Alignment
    Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024. (Research Track) (acceptance rate: around 20%)

  10. IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
    Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024. (Research Track) (acceptance rate: around 20%)

  11. Causal Inference with Latent Variables: Recent Advances and Future Prospectives
    Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024. (Tutorial Track and Survey Paper)

  12. Knowledge Graph-Enhanced Large Language Models via Path Selection
    Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li
    Annual Meeting of the Association for Computational Linguistics (ACL Findings), 2024.

  13. FastGAS: Fast Graph-based Annotation Selection for In-Context Learning
    Zihan Chen, Song Wang, Cong Shen, Jundong Li
    Annual Meeting of the Association for Computational Linguistics (ACL Findings), 2024.

  14. Verification of Machine Unlearning is Fragile
    Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li
    International Conference on Machine Learning (ICML), 2024.

  15. Towards Certified Unlearning for Deep Neural Networks
    Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li
    International Conference on Machine Learning (ICML), 2024.

  16. Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
    Haochen Liu, Song Wang, Chen Chen, Jundong Li
    Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.

  17. PyGDebias: A Python Library for Debiasing in Graph Learning
    Yushun Dong, Zhenyu Lei, Zaiyi Zheng, Song Wang, Jing Ma, Alex Jing Huang, Chen Chen, Jundong Li
    The Web Conference (formerly WWW), 2024. (demo paper)

  18. Collaborative Large Language Model for Recommender Systems
    Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
    The Web Conference (formerly WWW), 2024. (acceptance rate: 20.2%)

  19. Adversarial Attacks on Fairness of Graph Neural Networks
    Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li
    International Conference on Learning Representations (ICLR), 2024. (acceptance rate: 31%)

  20. SD-Attack: Targeted Spectral Attacks on Graphs
    Xianren Zhang, Jing Ma, Yushun Dong, Chen Chen, Min Gao, Jundong Li
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.

  21. Interpreting Pretrained Language Models via Concept Bottlenecks
    Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, Huan Liu
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.
    Best Paper Award

  22. Personalized Federated Learning with Attention-based Client Selection
    Zihan Chen, Jundong Li, Cong Shen
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

  23. Federated Graph Learning with Graphless Clients
    Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li
    Transactions on Machine Learning Research (TMLR), 2024. (To Appear)

  24. Knowledge Editing for Large Language Models: A Survey
    Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li
    ACM Computing Surveys (CSUR), 2024. (To Appear)

  25. Graph Learning for Particle Accelerator Operations
    Song Wang, Chris Tennant, Daniel Moser, Theo Larrieu, Jundong Li
    Frontiers in Big Data, section Data Mining and Management, 2024. (To Appear)

  26. Semi-Supervised Graph Contrastive Learning with Virtual Adversarial Augmentation
    Yixiang Dong, Minnan Luo, Jundong Li, Ziqi Liu, and Qinghua Zheng
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024. (To Appear)

2023

  1. Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance
    Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li
    Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), 2023.

  2. Generative Few-shot Graph Classification: An Adaptive Perspective
    Song Wang, Jundong Li
    Asilomar Conference on Signals, Systems and Computers (Asilomar), 2023. (Invited Paper)

  3. GiGaMA: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction
    Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2023. (acceptance rate: 354/1472=24%)

  4. Fair Few-shot Learning with Auxiliary Sets
    Song Wang, Jing Ma, Lu Cheng, Jundong Li
    European Conference on Artificial Intelligence (ECAI), 2023. (acceptance rate: 24% out of 1631 submissioins)

  5. Learning Causal Effects on Hypergraphs (Extended Abstract)
    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan
    International Joint Conference on Artificial Intelligence (IJCAI), 2023. (Best Papers from Sister Conferences Track)

  6. Learning for Counterfactual Fairness from Observational Data
    Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Research Track) (acceptance rate: 313/1416=22.1%)

  7. Path-Specific Counterfactual Fairness for Recommender Systems
    Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Research Track) (acceptance rate: 313/1416=22.1%)

  8. Federated Few-shot Learning
    Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Research Track) (acceptance rate: 313/1416=22.1%)

  9. Contrastive Meta-Learning for Few-shot Node Classification
    Song Wang, Zhen Tan, Huan Liu, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Research Track) (acceptance rate: 313/1416=22.1%)

  10. Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective
    Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Research Track) (acceptance rate: 313/1416=22.1%)

  11. A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection
    Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory R Madden, Daniel Borrajo, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Applied Data Science Track) (acceptance rate: 184/725=25.4%)

  12. BIC: Twitter Bot Detection with Text-Graph Interaction and Semantic Consistency
    Zhenyu Lei, Herun Wan, Wenqian Zhang, Shangbin Feng, Zilong Chen, Jundong Li, Qinghua Zheng, Minnan Luo
    Annual Meeting of the Association for Computational Linguistics (ACL), 2023.

  13. When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?
    Yushun Dong, Jundong Li, Tobias Schnabel
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023. (Full paper) (acceptance rate: 165/822=20.1%)

  14. Spatial-Temporal Networks for Antibiogram Pattern Prediction
    Xingbo Fu, Chen Chen, Yushun Dong, Anil Vullikanti, Eili Klein, Gregory Madden, Jundong Li
    IEEE International Conference on Healthcare Informatics (ICHI), 2023.

  15. KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion
    Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo
    The Web Conference (formerly WWW), 2023. (acceptance rate: 19.2%)

  16. RELIANT: Fair Knowledge Distillation for Graph Neural Networks
    Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li
    SIAM International Conference on Data Mining (SDM), 2023. (acceptance rate: 27.4%)

  17. A Deep Multi-View Framework for Anomaly Detection on Attributed Networks (Extended Abstract)
    Zhen Peng, Minnan Luo, Jundong Li, Luguo Xue, Qinghua Zheng
    IEEE International Conference on Data Engineering (ICDE), 2023.

  18. Interpreting Unfairness in Graph Neural Networks via Training Node Attribution
    Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
    AAAI Conference on Artificial Intelligence (AAAI), 2023. (acceptance rate: 1721/8777=19.6%)

  19. Few-shot Node Classification with Extremely Weak Supervision
    Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2023. (acceptance rate: 123/690=17.82%)

  20. Learning Hierarchical Task Structures for Few-shot Graph Classification
    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2023. (To Appear)

  21. Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification
    Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2023. (To Appear)

  22. Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data
    Qiang Huang, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2023. (To Appear)

  23. Second-Order Unsupervised Feature Selection via Knowledge Contrastive Distillation
    Han Yue, Jundong Li, Hongfu Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023. (To Appear)

  24. Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning
    Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang
    Transactions on Machine Learning Research (TMLR), 2023. (To Appear)
    (Also appear in GLFrontiers workshop in NeurIPS 2022)

  25. Fairness in Graph Mining: A Survey
    Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (To Appear)

  26. Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective
    Jihong Wang, Minnan Luo, Jundong Li, Ziqi Liu, Jun Zhou, Qinghua Zheng
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (To Appear)

  27. Self-Supervised Learning for Recommender Systems: A Survey
    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, Zi Huang
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (To Appear)

  28. Collaborative Graph Neural Networks for Attributed Network Embedding
    Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (To Appear)

  29. OEC: An Online Ensemble Classifier for Mining Data Stream with Noisy Labels
    Ling Jian, Kai Shao, Ying liu, Jundong Li, Xijun Liang
    Data Mining and Knowledge Discovery (DMKD), 2023. (To Appear)

  30. Marginal Nodes Matter: Towards Structure Fairness in Graphs
    Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou
    SIGKDD Explorations, 2023. (To Appear)

  31. Causal Inference and Recommendations
    Yaochen Zhu, Jing Ma, Jundong Li
    In Machine Learning for Causal Inference (edited by Zhixuan Chu, Sheng Li), Springer, 2023.
    (Preprint version available on Arxiv)

  32. Causal Inference on Graphs
    Jing Ma, Ruocheng Guo, Jundong Li
    In Machine Learning for Causal Inference (edited by Zhixuan Chu, Sheng Li), Springer, 2023.

2022

  1. Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification
    Zhen Tan*, Song Wang*, Kaize Ding, Jundong Li, Huan Liu
    Learning on Graphs Conference (LOG), 2022.

  2. Graph Few-shot Learning with Task-specific Structures
    Song Wang, Chen Chen, Jundong Li
    Neural Information Processing Systems (NeurIPS), 2022. (acceptance rate: 25.6%)

  3. CLEAR: Generative Counterfactual Explanations on Graphs
    Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
    Neural Information Processing Systems (NeurIPS), 2022. (acceptance rate: 25.6%)

  4. Benchmarking Node Outlier Detection on Static Attributed Graphs
    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, Philip S. Yu
    Neural Information Processing Systems (NeurIPS), 2022. (Datasets and Benchmarks Track)

  5. TwiBot-22: Towards Graph-Based Twitter Bot Detection
    Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo
    Neural Information Processing Systems (NeurIPS), 2022. (Datasets and Benchmarks Track)

  6. SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training
    Qiang Huang, Jing Ma, Jundong Li, Huiyan Sun, Yi Chang
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022. (acceptance rate: 242/932=25.97%)

  7. Task-Adaptive Few-shot Node Classification
    Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (acceptance rate: 254/1695=14.99%)

  8. On Structural Explanation of Bias in Graph Neural Networks
    Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (acceptance rate: 254/1695=14.99%)

  9. Learning Causal Effects on Hypergraphs
    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (acceptance rate: 254/1695=14.99%)
    Best Research Paper Award

  10. GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks
    Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (acceptance rate: 254/1695=14.99%)

  11. Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage
    Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (acceptance rate: 254/1695=14.99%)

  12. FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs
    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
    International Joint Conference on Artificial Intelligence (IJCAI), 2022. (acceptance rate: ~15% out of 4535 submissions)

  13. Few-Shot Learning on Graphs: A Survey
    Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V Chawla, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2022. (Survey Track) (acceptance rate: 38/209=18.18%)

  14. KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media
    Wenqian Zhang, Shangbin Feng, Zilong Chen, Zhenyu Lei, Jundong Li, Minnan Luo
    North American Chapter of the Association for Computational Linguistic (NAACL), 2022.

  15. Empowering Next POI Recommendation with Multi-Relational Modeling
    Zheng Huang, Jing Ma, Yushun Dong, Natasha Foutz, Jundong Li
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022. (short paper) (acceptance rate: 165/667=24.73%)

  16. EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks
    Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li
    The Web Conference (formerly WWW), 2022. (acceptance rate: 323/1822=17.73%)

  17. Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US
    Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li
    The Web Conference (formerly WWW), 2022. (acceptance rate: 323/1822=17.73%)

  18. Unbiased Graph Embedding with Biased Graph Observations
    Nan Wang, Lu Lin, Jundong Li, Hongning Wang
    The Web Conference (formerly WWW), 2022. (acceptance rate: 323/1822=17.73%)

  19. Geometric Graph Representation Learning via Maximizing Rate Reduction
    Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu
    The Web Conference (formerly WWW), 2022. (acceptance rate: 323/1822=17.73%)

  20. Contrastive Attributed Network Anomaly Detection with Data Augmentation
    Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, Jundong Li
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022. (acceptance rate: 121/627=19.30%)

  21. Learning Fair Node Representations with Graph Counterfactual Fairness
    Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2022. (acceptance rate: 159/786=20.23%)

  22. Learning Causality with Graphs
    Jing Ma, Jundong Li
    AI Magazine, 2022.

  23. Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications
    Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li
    SIGKDD Explorations, 2022.
    (Also appear in FedGraph2022 workshop in CIKM 2022)

  24. Learning Representations by Graphical Mutual Information Estimation and Maximization
    Zhen Peng, Minnan Luo, Wenbing Huang, Jundong Li, Qinghua Zheng, Fuchun Sun, Junzhou Huang
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.

  25. Gray-Box Shilling Attack: An Adversarial Learning Approach
    Zongwei Wang, Min Gao, Jundong Li, Junwei Zhang, Jiang Zhong
    ACM Transactions on Intelligent Systems and Technology (TIST), 2022.

2021

  1. AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter
    Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li
    ACM International Conference on Information and Knowledge Management (CIKM), 2021. (full paper) (acceptance rate: 271/1251=21.66%)

  2. REFORM: Error-Aware Few-Shot Knowledge Graph Completion
    Song Wang, Xiao Huang, Chen Chen, Liang Wu, Jundong Li
    ACM International Conference on Information and Knowledge Management (CIKM), 2021. (full paper) (acceptance rate: 271/1251=21.66%)

  3. Double-Scale Self-Supervised Hypergraph Convolutional Network for Group Recommendation
    Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li, Hongzhi Yin
    ACM International Conference on Information and Knowledge Management (CIKM), 2021. (full paper) (acceptance rate: 271/1251=21.66%)

  4. Fairness-Aware Unsupervised Feature Selection
    Xiaoying Xing, Hongfu Liu, Chen Chen, Jundong Li
    ACM International Conference on Information and Knowledge Management (CIKM), 2021. (short paper) (acceptance rate: 177/626=28.27%)

  5. SATAR: A Self-supervised Approach to Twitter Account Representation Learning and its Application in Bot Detection
    Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo
    ACM International Conference on Information and Knowledge Management (CIKM), 2021. (applied paper) (acceptance rate: 69/290=23.79%)

  6. TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark
    Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo
    ACM International Conference on Information and Knowledge Management (CIKM), 2021. (resource track) (acceptance rate: 26/80=32.50%)

  7. Individual Fairness for Graph Neural Networks: A Ranking based Approach
    Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021. (acceptance rate: 238/1541=15.44%)

  8. Unsupervised Graph Alignment with Wasserstein Distance Discriminator
    Ji Gao, Xiao Huang, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021. (acceptance rate: 238/1541=15.44%)

  9. Multi-Cause Effect Estimation with Disentangled Confounder Representation
    Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
    International Joint Conference on Artificial Intelligence (IJCAI), 2021. (acceptance rate: 587/4204=13.96%)

  10. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation [code]
    Junliang Yu, Hongzhi Yin, Jundong Li, Qingyong Wang, Nguyen Quoc Viet Hung, Xiangliang Zhang
    The Web Conference (formerly WWW), 2021. (acceptance rate: 357/1736=20.56%)

  11. Deconfounding with Networked Observational Data in a Dynamic Environment [code]
    Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2021. (acceptance rate: 112/603=18.57%)

  12. Toward User Engagement Optimization in 2D Presentation
    Liang Wu, Mihajlo Grbovic, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2021. (acceptance rate: 112/603=18.57%)

  13. Automated Generation of Disaster Response Networks through Information Extraction
    Yitong Li, Duoduo Liao, Jundong Li, Wenying Ji
    Information Systems for Crisis Response And Management (ISCRAM), 2021.

  14. Cross-domain Anomaly Detection on Attributed Networks
    Kaize Ding, Kai Shu, Xuan Shan, Jundong Li, and Huan Liu
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

  15. Line Graph Neural Networks for Link Prediction [code]
    Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.

  16. Rumor2vec: A Rumor Detection Framework with Joint Text and Propagation Structure Representation Learning
    Kefei Tu, Chen Chen, Chunyuan Hou, Jing Yuan, Jundong Li, Xiaojie Yuan
    Information Sciences (IS), 2021.

  17. Anomaly Detection aided Budget Online Classification for Imbalanced Data Streams
    Xijun Liang, Xiaoxin Song, Kai Qi, Jundong Li, Jinyu Liu, Ling Jian
    IEEE Intelligent Systems, 2021.

2020

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

  2. A Scalable Social Tie Strength Measuring
    Yan Zhong, Xiao Huang, Jundong Li and Xia Hu
    IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2020.

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

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

  5. Scalable Attack on Graph Data by Injecting Vicious Nodes
    Jihong Wang, Minnan Luo, Fnu Suya, Jundong Li, Zijiang Yang, Qinghua Zheng
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2020
    Data Mining and Knowledge Discovery, 2020 (Journal Track of ECMLPKDD 2020).

  6. Inductive Anomaly Detection on Attributed Networks
    Kaize Ding, Jundong Li, Nitin Agarwal, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2020.

  7. IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data
    Ruocheng Guo, Jundong Li, Yichuan Li, K. Selcuk Candan, Adrienne Raglin, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2020.

  8. Unsupervised Hierarchical Feature Selection on Networked Data
    Yuzhe Zhang, Chen Chen, Minnan Luo, Jundong Li, Caixia Yan, Qinghua Zheng
    International Conference on Database Systems for Advanced Applications (DASFAA), 2020.

  9. Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
    Ruocheng Guo, Jundong Li, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2020.

  10. Tracking Disaster Footprints with Social Stream Data
    Lu Cheng, Jundong Li, K. Selcuk Candan, Huan Liu
    AAAI Conference on Artificial Intelligence (AAAI), 2020.

  11. Learning Individual Causal Effects from Networked Observational Data [code]
    Ruocheng Guo, Jundong Li, Huan Liu
    ACM International Conference on Web Search and Data Mining (WSDM), 2020.

  12. A Survey of Learning Causality with Data: Problems and Methods
    Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu
    ACM Computing Surveys (CSUR), 2020.

  13. Enhancing Social Recommendation with Adversarial Graph Convolutional Networks
    Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, Lizhen Cui
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.

  14. A Deep Multi-View Framework for Anomaly Detection on Attributed Networks
    Zhen Peng, Minnan Luo, Jundong Li, Luguo Xue, Qinghua Zheng
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.

  15. LookCom: Learning Optimal Network for Community Detection
    Yixiang Dong, Minnan Luo, Jundong Li, Deng Cai, Qinghua Zheng
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.

  16. Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective
    Min Gao, Junwei Zhang, Junliang Yu, Jundong Li, Junhao Wen, Qingyu Xiong
    Information Sciences (IS), 2020.

  17. Incremental One-Class Collaborative Filtering with Co-Evolving Side Networks
    Chen Chen, Yinglong Xia, Hui Zang, Jundong Li, Huan Liu, Hanghang Tong
    Knowledge and Information Systems (KAIS), 2020.

  18. Nonlinear Feature Selection on Attributed Networks
    Zhongping Lin, Minnan Luo, Zhen Peng, Jundong Li, Qinghua Zheng
    Neurocomputing, 2020.

  19. Using Machine Learning to Predict Ovarian Cancer
    Mingyang Liu, Zhenjiang Fan, Bin Xu, Lujun Chen, Xiao Zheng, Jundong Li, Taieb Znati, Qi Mi, Jingting Jiang
    International Journal of Medical Informatics (IJMI), 2020.

2019

  1. Generating Reliable Friends via Adversarial Training to Improve Social Recommendation [code]
    Junliang Yu, Min Gao, Hongzhi Yin, Jundong Li, Chongming Gao, Qinyong Wang
    IEEE International Conference on Data Mining (ICDM), 2019.

  2. SpecAE: Spectral Autoencoder for Anomaly Detection in Attributed Networks (short paper)
    Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou
    ACM International Conference on Information and Knowledge Management (CIKM), 2019.

  3. Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation
    Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, Huan Liu
    IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019.

  4. Adaptive Unsupervised Feature Selection on Attributed Networks
    Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019.

  5. PI-Bully: Personalized Cyberbullying Detection with Peer Influence
    Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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

  7. Deep Structured Cross-Modal Anomaly Detection
    Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu
    International Joint Conference on Neural Networks (IJCNN), 2019.

  8. Deep Anomaly Detection on Attributed Networks
    Kaize Ding, Jundong Li, Rohit Bhanushali, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2019.

  9. Robust Factorization Machine: A Doubly Capped Norms Minimization
    Chenghao Liu, Teng Zhang, Jundong Li, Jianwen Yin, Peilin Zhao, Jianling Sun, Steven Hoi
    SIAM International Conference on Data Mining (SDM), 2019.

  10. Online Collaborative Filtering with Implicit Feedback
    Jianwen Yin, Chenghao Liu, Jundong Li, Bing Tian Dai, Yun-chen Chen, Min Wu, Jianling Sun
    International Conference on Database Systems for Advanced Applications (DASFAA), 2019.

  11. Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search
    Zhen Peng, Minnan Luo, Jundong Li, Chen Chen, Qinghua Zheng
    International Conference on Database Systems for Advanced Applications (DASFAA), 2019.

  12. Anomaly Detection in Time-Evolving Attributed Networks (poster paper)
    Luguo Xue, Minnan Luo, Zhen Peng, Jundong Li, Yan Chen, Jun Liu
    International Conference on Database Systems for Advanced Applications (DASFAA), 2019.

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

  14. XBully: Cyberbullying Detection within a Multi-Modal Context
    Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, Huan Liu
    ACM International Conference on Web Search and Data Mining (WSDM), 2019.

  15. Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics [video]
    Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski
    IEEE Visualization Conference (VIS), 2019
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 26(1): 1075-1085, 2020.

2018

  1. Interactive Unknowns Recommendation in E-Learning Systems
    Shan-Yun Teng, Jundong Li, Lo-Pang-Yun Ting, Kun-Ta Chuang, Huan Liu
    IEEE International Conference on Data Mining (ICDM), 2018.

  2. Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation [code]
    Junliang Yu, Min Gao, Jundong Li, Hongzhi Yin, Huan Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2018.

  3. On Interpretation of Network Embedding via Taxonomy Induction [code]
    Ninghao Liu, Xiao Huang, Jundong Li, Xia Hu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.

  4. INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process
    Ruocheng Guo, Jundong Li, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI-ECAI), 2018.

  5. ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks
    Zhen Peng, Minnan Luo, Jundong Li, Huan Liu, Qinghua Zheng
    International Joint Conference on Artificial Intelligence (IJCAI-ECAI), 2018.

  6. Understanding and Predicting Delay in Reciprocal Relations
    Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang, Huan Liu
    The Web Conference (formerly WWW), 2018.

  7. Multi-Layered Network Embedding [errata]
    Jundong Li*, Chen Chen*, Hanghang Tong, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2018.

  8. Toward Relational Learning with Misinformation
    Liang Wu, Jundong Li, Fred Morstatter, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2018.

  9. Unsupervised Personalized Feature Selection [errata]
    Jundong Li, Liang Wu, Harsh Dani, Huan Liu
    AAAI Conference on Artificial Intelligence (AAAI), 2018.

  10. Personalized Privacy-Preserving Social Recommendation
    Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang
    AAAI Conference on Artificial Intelligence (AAAI), 2018.

  11. Streaming Link Prediction on Dynamic Attributed Networks
    Jundong Li, Kewei Cheng, Liang Wu, Huan Liu
    ACM International Conference on Web Search and Data Mining (WSDM), 2018.

  12. Exploring Expert Cognition for Attributed Network Embedding [code]
    Xiao Huang, Qingquan Song, Jundong Li, Xia Hu
    ACM International Conference on Web Search and Data Mining (WSDM), 2018.

  13. Towards Privacy Preserving Social Recommendation under Personalized Privacy Settings
    Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang
    World Wide Web Journal (WWWJ), 2018.

  14. A General Embedding Framework for Heterogeneous Information Learning in Large-scale Networks
    Xiao Huang, Jundong Li, Na Zou, Xia Hu
    ACM Transactions on Knowledge Discovery from Data (TKDD), 12(6): 70:1-70:24, 2018.

  15. Exploiting Multilabel Information for Noise-Resilient Feature Selection
    Ling Jian, Jundong Li, Huan Liu
    ACM Transactions on Intelligent Systems and Technology (TIST), 9(5): 52:1-52:23, 2018.

  16. Toward Online Node Classification on Streaming Networks
    Ling Jian, Jundong Li, Huan Liu
    Data Mining and Knowledge Discovery (DMKD), 32(1): 231-257, 2018.

  17. Feature Selection: A Data Perspective (among the most cited papers of CSUR within 5 years)
    Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang, Huan Liu
    ACM Computing Surveys (CSUR), 50(6): 94:1-94:45, 2018.

2017

  1. Attributed Network Embedding for Learning in a Dynamic Environment (the most cited paper of CIKM 2017)
    Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2017.

  2. Sentiment Informed Cyberbullying Detection in Social Media
    Harsh Dani, Jundong Li, Huan Liu
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2017.

  3. Radar: Residual Analysis for Anomaly Detection in Attributed Networks
    Jundong Li, Harsh Dani, Xia Hu, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2017.

  4. Reconstruction-based Unsupervised Feature Selection: An Embedded Approach
    Jundong Li, Jiliang Tang, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2017.

  5. Unsupervised Feature Selection in Signed Social Networks
    Kewei Cheng*, Jundong Li*, Huan Liu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017.

  6. Toward Personalized Relational Learning [errata]
    Jundong Li, Liang Wu, Osmar R. Zaïane, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2017.

  7. Gleaning Wisdom From The Past: Early Detection of Emerging Rumors in Social Media
    Liang Wu, Jundong Li, Xia Hu, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2017.

  8. Accelerated Attributed Network Embedding (the most cited papers of SDM within 5 years)
    Xiao Huang, Jundong Li, Xia Hu
    SIAM International Conference on Data Mining (SDM), 2017.

  9. Understanding and Discovering Deliberate Self-harm Content in Social Media
    Yilin Wang, Jiliang Tang, Jundong Li, Baoxin Li, Yali Wan, Clayton Mellina, Neil O'Hare, Yi Chang
    International World Wide Web Conference (WWW), 2017.

  10. Unsupervised Sentiment Analysis with Signed Social Networks
    Kewei Cheng, Jundong Li, Jiliang Tang, Huan Liu
    AAAI Conference on Artificial Intelligence (AAAI), 2017.

  11. Label Informed Attributed Network Embedding (among the most cited papers of WSDM within 5 years)
    Xiao Huang, Jundong Li, Xia Hu
    ACM International Conference on Web Search and Data Mining (WSDM), 2017.

  12. Challenges of Feature Selection for Big Data Analytics
    Jundong Li, Huan Liu
    IEEE Intelligent System, 32(2): 9-15, 2017.

  13. Exploiting Expertise Rules for Statistical Data-Driven Modeling
    Ling Jian, Jundong Li, Shihua Luo
    IEEE Transactions on Industrial Electronics (TIE), 64(11): 8647-8656, 2017.

  14. Budget Online Learning Algorithm for Least Squares SVM
    Ling Jian, Shuqian Shen, Jundong Li, Xijun Liang, Lei Li
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 28(9): 2076-2087, 2017.

  15. Exploiting Statistically Significant Dependent Rules for Associative Classification
    Jundong Li, Osmar R. Zaïane
    Intelligent Data Analysis: An International Journal, 21(5): 1155-1172, 2017.

2016

  1. Toward Time-Evolving Feature Selection on Dynamic Networks (short paper)
    Jundong Li, Xia Hu, Ling Jian, Huan Liu
    IEEE International Conference on Data Mining (ICDM), 2016.

  2. FeatureMiner: A Tool for Interactive Feature Selection (demo paper) [demo]
    Kewei Cheng, Jundong Li, Huan Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2016.

  3. Multi-Label Informed Feature Selection
    Ling Jian*, Jundong Li*, Kai Shu, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2016.

  4. Robust Unsupervised Feature Selection on Networked Data
    Jundong Li, Xia Hu, Liang Wu, Huan Liu
    SIAM International Conference on Data Mining (SDM), 2016.

  5. On Discovering Co-Location Patterns in Datasets: A Case Study of Pollutants and Child Cancers
    Jundong Li, Aibek Adilmagambetov, M. Shazan M. Jabbar, Osmar R. Zaïane, Alvaro Osornio-Vargas, Osnat Wine
    GeoInformatica, 20(4): 651-692, 2016.

2015 and earlier

  1. Unsupervised Streaming Feature Selection in Social Media
    Jundong Li, Xia Hu, Jiliang Tang, Huan Liu
    ACM International Conference on Information and Knowledge Management (CIKM), 2015.

  2. Associative Classification with Statistically Significant Positive and Negative Rules
    Jundong Li, Osmar R. Zaïane
    ACM International Conference on Information and Knowledge Management (CIKM), 2015.

  3. Discovering Statistically Significant Co-location Rules in Datasets with Extended Spatial Objects
    Jundong Li, Osmar R. Zaïane, Alvaro Osornio-Vargas
    International Conference on Data Warehousing and Knowledge Discovery (DaWaK), 2014.

  4. Active Learning Strategies for Semi-Supervised DBSCAN
    Jundong Li, Jörg Sander, Ricardo G.J.B Campello, Arthur Zimek
    Canadian Conference on Artificial Intelligence (AI), 2014.

  5. Negative Association Rules
    Luiza Antonie, Jundong Li, Osmar R. Zaïane
    In Frequent Pattern Mining (edited by Charu C. Aggarwal, Jiawei Han), Springer, 2014.