Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients. - Chenrui Wu 002; Zexi Li 001; Fangxin Wang 001; Chao Wu 001 (ICME, 2023)

Cluster-driven GNN-based Federated Recommendation with Biased Message Dropout. - Rongyu Zhang; Yun Chen; Chenrui Wu 002; Fangxin Wang 001 (ICME, 2023)

Optimizing Efficient Personalized Federated Learning with Hypernetworks at Edge. - Rongyu Zhang; Yun Chen; Chenrui Wu 002; Fangxin Wang 001; Jiangchuan Liu (IEEE Netw., 2023)

FedAB: Truthful Federated Learning With Auction-Based Combinatorial Multi-Armed Bandit. - Chenrui Wu 002; Yifei Zhu 001; Rongyu Zhang; Yun Chen; Fangxin Wang 001; Shuguang Cui (IEEE Internet Things J., 2023)

FedTSA: A Cluster-Based Two-Stage Aggregation Method for Model-Heterogeneous Federated Learning. - Boyu Fan; Chenrui Wu 002; Xiang Su; Pan Hui 001 (ECCV (83), 2024)

Spatio-temporal Heterogeneous Federated Learning for Time Series Classification with Multi-view Orthogonal Training. - Chenrui Wu 002; Haishuai Wang; Xiang Zhang 012; Zhen Fang 001; Jiajun Bu (ACM Multimedia, 2024)

Multi-Level Personalized Federated Learning on Heterogeneous and Long-Tailed Data. - Rongyu Zhang; Yun Chen; Chenrui Wu 002; Fangxin Wang 001; Bo Li 001 (IEEE Trans. Mob. Comput., 2024)

Cluster Based Heterogeneous Federated Foundation Model Adaptation and Fine-Tuning. - Xianda Wang; Yaqi Qiao; Duo Wu; Chenrui Wu 002; Fangxin Wang 001 (AAAI, 2025)