SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition. - Haolin Wang 002; Xuefeng Liu 001; Jianwei Niu 002; Shaojie Tang 001 (INFOCOM, 2023)

Unlocking the Potential of Federated Learning for Deeper Models. - Haolin Wang 002; Xuefeng Liu 001; Jianwei Niu 002; Shaojie Tang 001; Jiaxing Shen (CoRR, 2023)

Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-rank Decomposition. - Xinghao Wu; Xuefeng Liu 001; Jianwei Niu 002; Haolin Wang 002; Shaojie Tang 001; Guogang Zhu; Hao Su (ACM Multimedia, 2024)

Why Go Full? Elevating Federated Learning Through Partial Network Updates. - Haolin Wang 002; Xuefeng Liu 001; Jianwei Niu 002; Wenkai Guo; Shaojie Tang 001 (NeurIPS, 2024)

Dataset-adaptive and bias-constrained brain age estimation using pyramid squeeze and excitation transformer. - Yixiao Hu; Haolin Wang 002; Jiaxiang Cao; Baobin Li (Neurocomputing, 2025)