Jun Wu

Jun Wu

Assistant Professor

Publications

You can also find my articles on my Google Scholar profile.

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

Heterogeneous Machine Learning

  1. 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)

  2. 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)

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

  4. 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)

  5. 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)