Aligning before aggregating: Enabling cross-domain federated learning via consistent feature extraction G Zhu, X Liu, S Tang, J Niu 2022 IEEE 42nd International Conference on Distributed Computing Systems …, 2022 | 6 | 2022 |
ChannelFed: Enabling Personalized Federated Learning via Localized Channel Attention K Zheng, X Liu, G Zhu, X Wu, J Niu GLOBECOM 2022-2022 IEEE Global Communications Conference, 2987-2992, 2022 | 3 | 2022 |
FedLoRA: When Personalized Federated Learning Meets Low-Rank Adaptation X Wu, X Liu, J Niu, H Wang, S Tang, G Zhu | 2 | 2023 |
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration X Wu, X Liu, J Niu, G Zhu, S Tang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 2 | 2023 |
A lightweight solution of industrial computed tomography with convolutional neural network G Zhu, J Fu NDT & E International 116, 102347, 2020 | 2 | 2020 |
Aligning before Aggregating: Enabling Communication Efficient Cross-Domain Federated Learning via Consistent Feature Extraction G Zhu, X Liu, S Tang, J Niu IEEE Transactions on Mobile Computing, 2023 | 1 | 2023 |
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning G Zhu, X Liu, X Wu, S Tang, C Tang, J Niu, H Su arXiv preprint arXiv:2405.19789, 2024 | | 2024 |
A deep learning reconstruction framework for low dose phase contrast computed tomography via inter-contrast enhancement C Zhang, G Zhu, J Fu, G Zhao Measurement 219, 113247, 2023 | | 2023 |
Take Your Pick: Enabling Effective Personalized Federated Learning within Low-dimensional Feature Space G Zhu, X Liu, S Tang, J Niu, X Wu, J Shen arXiv preprint arXiv:2307.13995, 2023 | | 2023 |