Conferences
- Distributional Network of Networks for Modeling Data Heterogeneity
Jun Wu, Jingrui He, Hanghang Tong
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2024)
[PDF][Code] - BOBA: Byzantine-Robust Federated Learning with Label Skewness
Wenxuan Bao, Jun Wu, Jingrui He
27th International Conference on Artificial Intelligence and Statistics (AISTATS-2024)
[PDF][Code] - Graph-Structured Gaussian Processes for Transferable Graph Learning
Jun Wu, Elizabeth Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He
Thirty-Seventh Conference on Neural Information Processing Systems (NeurIPS-2023)
[PDF][Code] - Personalized Federated Learning with Parameter Propagation
Jun Wu, Wenxuan Bao, Elizabeth Ainsworth, Jingrui He
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2023)
[PDF][Slides][Poster][Code] - Optimizing the Collaboration Structure in Cross-silo Federated Learning
Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He
Fortieth International Conference on Machine Learning (ICML-2023)
[PDF][Code] - Non-IID Transfer Learning on Graphs
Jun Wu, Jingrui He, Elizabeth Ainsworth
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2023)
[PDF][Poster][Code] - Adaptive Knowledge Transfer on Evolving Domains
Jun Wu, Hanghang Tong, Elizabeth Ainsworth, Jingrui He
IEEE International Conference on Big Data (BigData-2022)
[PDF][Slides] - Distribution-Informed Neural Networks for Domain Adaptation Regression
Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth Ainsworth
Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS-2022)
[PDF][Slides][Poster][Code] - Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning
Jun Wu*, Yao Zhou*, Haixun Wang, Jingrui He (*Equal Contribution)
ACM International Conference on Information and Knowledge Management (CIKM-2022)
[PDF][Slides][Poster][Code] - Domain Adaption with Dynamic Open-Set Targets
Jun Wu, Jingrui He
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2022)
[PDF][Slides][Poster][Code] - A Unified Meta-Learning Framework for Dynamic Transfer Learning
Jun Wu, Jingrui He
International Joint Conference on Artificial Intelligence (IJCAI-2022)
[PDF][arXiv][Slides][Code] - Indirect Invisible Poisoning Attacks on Domain Adaptation
Jun Wu, Jingrui He
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2021)
[PDF][Slides][Poster][Code] - PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network
Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi, Evren Korpeoglu, Kannan Achan, Jingrui He
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2021)
[PDF][Code] - DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
Jun Wu, Jingrui He, Jiejun Xu
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2019)
[PDF][Poster][Code] - Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy
Jun Wu, Jingrui He
ACM International Conference on Information and Knowledge Management (CIKM-2019)
[PDF][Poster][Code] - Textual Indicator Extraction from Aviation Accident Reports
Xue Hu, Jun Wu, Jingrui He
AIAA Aviation 2019 Forum
[PDF] - ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation
Jun Wu, Jingrui He, Yongming Liu
IEEE International Conference on Big Data (BigData-2018)
[PDF][Slides][Code]
Journals
- A Unified Framework for Adversarial Attacks on Multi-Source Domain Adaptation
Jun Wu, Jingrui He
IEEE Transactions on Knowledge and Data Engineering
[PDF] - Dynamic Transfer Learning with Progressive Meta-task Scheduler
Jun Wu, Jingrui He
Frontiers in Big Data, Rising Stars in Data Mining and Management 2022
[PDF]
Workshop
- Adaptive Transfer Learning for Plant Phenotyping
Jun Wu, Elizabeth Ainsworth, Sheng Wang, Kaiyu Guan, Jingrui He
Third International Workshop on Machine Learning for Cyber-Agricultural Systems (MLCAS-2021)
[PDF]