| Federated mutual learning T Shen, J Zhang, X Jia, F Zhang, G Huang, P Zhou, K Kuang, F Wu, C Wu arXiv preprint arXiv:2006.16765, 2020 | 170* | 2020 |
| Federated unsupervised representation learning F Zhang, K Kuang, L Chen, Z You, T Shen, J Xiao, Y Zhang, C Wu, F Wu, ... Frontiers of Information Technology & Electronic Engineering 24 (8), 1181-1193, 2023 | 161 | 2023 |
| Edge-cloud polarization and collaboration: A comprehensive survey for ai J Yao, S Zhang, Y Yao, F Wang, J Ma, J Zhang, Y Chu, L Ji, K Jia, T Shen, ... IEEE Transactions on Knowledge and Data Engineering 35 (7), 6866-6886, 2022 | 112 | 2022 |
| A graph-based power flow method for balanced distribution systems T Shen, Y Li, J Xiang Energies 11 (3), 511, 2018 | 101 | 2018 |
| Federated graph learning--a position paper H Zhang, T Shen, F Wu, M Yin, H Yang, C Wu arXiv preprint arXiv:2105.11099, 2021 | 67 | 2021 |
| Duet: A tuning-free device-cloud collaborative parameters generation framework for efficient device model generalization Z Lv, W Zhang, S Zhang, K Kuang, F Wang, Y Wang, Z Chen, T Shen, ... Proceedings of the ACM Web Conference 2023, 3077-3085, 2023 | 57 | 2023 |
| Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models D Zhu, Z Sun, Z Li, T Shen, K Yan, S Ding, K Kuang, C Wu arXiv preprint arXiv:2402.12048, 2024 | 24 | 2024 |
| FedDTG: Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks Z Zhang, T Shen, J Zhang, C Wu arXiv preprint arXiv:2201.03169, 2022 | 10 | 2022 |
| Retrieval-augmented mixture of lora experts for uploadable machine learning Z Zhao, L Gan, G Wang, Y Hu, T Shen, H Yang, K Kuang, F Wu arXiv preprint arXiv:2406.16989, 2024 | 5 | 2024 |
| Training-time neuron alignment through permutation subspace for improving linear mode connectivity and model fusion Z Li, Z Li, J Lin, T Shen, T Lin, C Wu arXiv preprint arXiv:2402.01342, 2024 | 4 | 2024 |
| Merging loras like playing lego: Pushing the modularity of lora to extremes through rank-wise clustering Z Zhao, T Shen, D Zhu, Z Li, J Su, X Wang, K Kuang, F Wu arXiv preprint arXiv:2409.16167, 2024 | 3 | 2024 |
| Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning Z Zhao, Y Zhou, D Zhu, T Shen, X Wang, J Su, K Kuang, Z Wei, F Wu, ... arXiv preprint arXiv:2501.15103, 2025 | | 2025 |
| FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning Z Jiang, J Xu, S Zhang, T Shen, J Li, K Kuang, H Cai, F Wu arXiv preprint arXiv:2412.18904, 2024 | | 2024 |
| Knowledge-Empowered, Collaborative, and Co-Evolving AI Models: The Post-LLM Roadmap F Wu, T Shen, T Bäck, J Chen, G Huang, Y Jin, K Kuang, M Li, C Lu, ... Engineering, 2024 | | 2024 |
| An Adaptive Aggregation Method for Federated Learning via Meta Controller T Shen, Z Li, Z Zhao, D Zhu, Z Lv, S Zhang, K Kuang, F Wu Proceedings of the 6th ACM International Conference on Multimedia in Asia …, 2024 | | 2024 |
| Deconfounded hierarchical multi-granularity classification Z Zhao, L Gan, T Shen, K Kuang, F Wu Computer Vision and Image Understanding 248, 104108, 2024 | | 2024 |
| Improving Group Connectivity for Generalization of Federated Deep Learning Z Li, J Lin, Z Li, D Zhu, R Ye, T Shen, T Lin, C Wu arXiv preprint arXiv:2402.18949, 2024 | | 2024 |
| Training-time Neuron Alignment for Improving Linear Mode Connectivity and Model Fusion Z Li, Z Li, T Shen, T Lin, C Wu | | |
Fei WuProfessor of Computer Science, Zhejiang Universitycs.zju.edu.cn의 이메일 확인됨