| 2025 | AAAI | ScaleOT: Privacy-utility-scalable Offsite-tuning with Dynamic LayerReplace and Selective Rank Compression. | Kai Yao, Zhaorui Tan, Tiandi Ye, Lichun Li, Yuan Zhao, Wenyan Liu, Wei Wang, Jianke Zhu |
| 2025 | CIKM | Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning. | Tiandi Ye, Wenyan Liu, Kai Yao, Lichun Li, Shangchao Su, Cen Chen, Xiang Li, Shan Yin, Ming Gao |
| 2024 | ICASSP | Federated Learning via Consensus Mechanism on Heterogeneous Data: A New Perspective on Convergence. | Shu Zheng, Tiandi Ye, Xiang Li, Ming Gao |
| 2024 | SDM | UPFL: Unsupervised Personalized Federated Learning towards New Clients. | Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao |
| 2023 | DASFAA | Robust Clustered Federated Learning. | Tiandi Ye, Senhui Wei, Jamie Cui, Cen Chen, Yingnan Fu, Ming Gao |
| 2023 | WWW | SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking. | Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao |
| 2022 | CIKM | Learning to Generalize in Heterogeneous Federated Networks. | Cen Chen, Tiandi Ye, Li Wang, Ming Gao |