Publications

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

Preprint Survey Papers

  1. Fairness in Graph Mining: A Survey
    Yushun Dong, Jing Ma, Chen Chen, Jundong Li

  2. Self-Supervised Learning for Recommender Systems: A Survey
    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, Zi Huang

Tutorials

  1. Machine Learning for Causal Inference
    Zhixuan Chu, Jing Ma, Jundong Li, Sheng Li
    AAAI Conference on Artificial Intelligence (AAAI), 2023

  2. Fairness in Graph Mining: Metrics, Algorithms, and Applications
    Yushun Dong, Jing Ma, Chen Chen, Jundong Li
    IEEE International Conference on Data Mining (ICDM), 2022

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

  4. Data Efficient Learning on Graphs
    Chuxu Zhang, Jundong Li, Meng Jiang
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021

  5. Learning From Networks: Algorithms, Theory, and Applications
    Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019

  6. Recent Advances in Feature Selection: A Data Perspective
    Jundong Li, Jiliang Tang, Huan Liu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017

2022

  1. 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 - non archived)

  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. 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. (To Appear)

  24. 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. (To Appear)

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. (To Appear)

  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. (To Appear)

  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. (To Appear)

  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. (To Appear)

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, (To Appear)

  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 (To Appear)

  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 (To Appear)

  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 (To Appear)

  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, (To Appear)

  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 (To Appear)

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

  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 (To Appear)

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 [code]
    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 [code]
    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 [code]
    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 [code] [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 (To Appear)

  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 [code] (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 [code]
    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 [code]
    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) [code]
    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) [code]
    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 [code]
    Ling Jian*, Jundong Li*, Kai Shu, Huan Liu
    International Joint Conference on Artificial Intelligence (IJCAI), 2016

  4. Robust Unsupervised Feature Selection on Networked Data [code]
    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