| 2025 | ICASSP | Distilling Generative-Discriminative Representations for Very Low-Resolution Face Recognition. | Junzheng Zhang, Weijia Guo, Bochao Liu, Ruixin Shi, Yong Li, Shiming Ge |
| 2024 | ECCV | Learning Differentially Private Diffusion Models via Stochastic Adversarial Distillation. | Bochao Liu, Pengju Wang, Shiming Ge |
| 2024 | IJCNN | Fusion of Current and Historical Knowledge for Personalized Federated Learning. | Pengju Wang, Bochao Liu, Weijia Guo, Yong Li, Shiming Ge |
| 2024 | SMC | Towards Personalized Federated Learning via Comprehensive Knowledge Distillation. | Pengju Wang, Bochao Liu, Weijia Guo, Yong Li, Shiming Ge |
| 2023 | IJCAI | Model Conversion via Differentially Private Data-Free Distillation. | Bochao Liu, Pengju Wang, Shikun Li, Dan Zeng, Shiming Ge |
| 2022 | MMSP | Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation. | Bochao Liu, Jianghu Lu, Pengju Wang, Junjie Zhang, Dan Zeng, Zhenxing Qian, Shiming Ge |
| 2018 | CIKM | Image Matters: Visually Modeling User Behaviors Using Advanced Model Server. | Tiezheng Ge, Liqin Zhao, Guorui Zhou, Keyu Chen, Shuying Liu, Huiming Yi, Zelin Hu, Bochao Liu, Peng Sun, Haoyu Liu, Pengtao Yi, Sui Huang, Zhiqiang Zhang, Xiaoqiang Zhu, Yu Zhang, Kun Gai |