Publications

Preprints

1. Trustworthy Transfer Learning: A Survey
   Jun Wu, Jingrui He

2. Single-Cell Data Integration and Cell Type Annotation through Contrastive Adversarial Open-set Domain Adaptation
   Fatemeh Aminzadeh*, Jun Wu*, Jingrui He, Morteza Saberi, Fatemeh Vafaee

Selected Publications (Full List)

Heterogeneous Machine Learning

1. Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
   Katherine Tieu, Dongqi Fu, Jun Wu, Jingrui He
   28th International Conference on Artificial Intelligence and Statistics (AISTATS-2025)

2. Distributional Network of Networks for Modeling Data Heterogeneity [Paper]
   Jun Wu, Jingrui He, Hanghang Tong
   30th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2024)

3. Graph-Structured Gaussian Processes for Transferable Graph Learning [Paper]
   Jun Wu, Elizabeth Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He
   Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS-2023)

4. Non-IID Transfer Learning on Graphs [Paper]
   Jun Wu, Jingrui He, Elizabeth Ainsworth
   Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2023)

5. Distribution-Informed Neural Networks for Domain Adaptation Regression [Paper]
   Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth Ainsworth
   36th Conference on Neural Information Processing Systems (NeurIPS-2022)

6. Domain Adaption with Dynamic Open-Set Targets [Paper]
   Jun Wu, Jingrui He
   28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2022)

Trustworthy Machine Learning

1. BOBA: Byzantine-Robust Federated Learning with Label Skewness [Paper]
   Wenxuan Bao, Jun Wu, Jingrui He
   27th International Conference on Artificial Intelligence and Statistics (AISTATS-2024)

2. Personalized Federated Learning with Parameter Propagation [Paper]
   Jun Wu, Wenxuan Bao, Elizabeth Ainsworth, Jingrui He
   29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2023)

3. Optimizing the Collaboration Structure in Cross-silo Federated Learning [Paper]
   Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He
   Fortieth International Conference on Machine Learning (ICML-2023)

4. Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning [Paper]
   Yao Zhou*, Jun Wu*, Haixun Wang, Jingrui He
   31st ACM International Conference on Information and Knowledge Management (CIKM-2022)

5. Indirect Invisible Poisoning Attacks on Domain Adaptation [Paper]
   Jun Wu, Jingrui He
   27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2021)

(* indicates equal contribution)