| Legodnn: block-grained scaling of deep neural networks for mobile vision R Han, Q Zhang, CH Liu, G Wang, J Tang, LY Chen Proceedings of the 27th Annual International Conference on Mobile Computing …, 2021 | 47 | 2021 |
| Fedknow: Federated continual learning with signature task knowledge integration at edge Y Luopan, R Han, Q Zhang, CH Liu, G Wang, LY Chen 2023 IEEE 39th International Conference on Data Engineering (ICDE), 341-354, 2023 | 23 | 2023 |
| Lightweight and accurate DNN-based anomaly detection at edge Q Zhang, R Han, G Xin, CH Liu, G Wang, LY Chen IEEE Transactions on Parallel and Distributed Systems 33 (11), 2927-2942, 2021 | 13 | 2021 |
| FedViT: Federated continual learning of vision transformer at edge X Zuo, Y Luopan, R Han, Q Zhang, CH Liu, G Wang, LY Chen Future Generation Computer Systems 154, 1-15, 2024 | 9 | 2024 |
| ElasticDNN: On-device Neural Network Remodeling for Adapting Evolving Vision Domains at Edge Q Zhang, R Han, CH Liu, G Wang, LY Chen IEEE Transactions on Computers, 2024 | 3 | 2024 |
| EdgeVisionBench: A Benchmark of Evolving Input Domains for Vision Applications at Edge Q Zhang, R Han, CH Liu, G Wang, LY Chen 2023 IEEE 39th International Conference on Data Engineering (ICDE), 3643-3646, 2023 | 3 | 2023 |
| An Empirical Analysis of Vision Transformer and CNN in Resource-Constrained Federated Learning X Zuo, Q Zhang, R Han Proceedings of the 2022 5th International Conference on Machine Learning and …, 2022 | 2 | 2022 |
| Loci: Federated Continual Learning of Heterogeneous Tasks at Edge Y Luopan, R Han, Q Zhang, X Zuo, CH Liu, G Wang, LY Chen IEEE Transactions on Parallel and Distributed Systems, 2025 | | 2025 |
| On Scheduling Early-exit Layers for Model Pipeline in 6G-based Edge Inference Y Liu, R Han, Q Zhang, H Hou, CH Liu, LY Chen IEEE Network, 2024 | | 2024 |
| EdgeTA: Neuron-grained Scaling of Foundation Models in Edge-side Retraining Q Zhang, R Han, CH Liu, G Wang, S Guo, LY Chen IEEE Transactions on Mobile Computing, 1-18, 2024 | | 2024 |
| RobustDA: Lightweight Robust Domain Adaptation for Evolving Data at Edge X Guo, X Zuo, R Han, J Ouyang, J Xie, CH Liu, Q Zhang, Y Guo, J Chen, ... IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2024 | | 2024 |
| Block-grained domain adaptation for neural networks at edge. XIN Gao-feng, LIU Yu-xiao, Z Qing-long, HAN Rui, LIU Ch Computer Engineering & Science/Jisuanji Gongcheng yu Kexue 46 (8), 2024 | | 2024 |