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Shangchao Su
Shangchao Su
在 fudan.edu.cn 的电子邮件经过验证
标题
引用次数
引用次数
年份
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
S Su, M Yang, B Li, X Xue
Proceedings of the AAAI Conference on Artificial Intelligence 38 (13), 15117 …, 2024
36*2024
Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models
M Yang, S Su, B Li, X Xue
Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16325 …, 2024
30*2024
One-shot federated learning without server-side training
S Su, B Li, X Xue
Neural Networks 164, 203-215, 2023
272023
Fedra: A random allocation strategy for federated tuning to unleash the power of heterogeneous clients
S Su, B Li, X Xue
European Conference on Computer Vision, 342-358, 2024
102024
Cross-domain federated object detection
S Su, B Li, C Zhang, M Yang, X Xue
2023 IEEE International Conference on Multimedia and Expo (ICME), 1469-1474, 2023
102023
One-Shot Federated Learning with Classifier-Guided Diffusion Models
M Yang, S Su, B Li, X Xue
arXiv preprint arXiv:2311.08870, 2023
42023
Privacy-preserving collaborative chinese text recognition with federated learning
S Su, H Yu, B Li, X Xue
arXiv preprint arXiv 2305, 2023
32023
FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models
M Yang, S Su, B Li, X Xue
ACM Multimedia 2024, 2024
22024
Domain Discrepancy Aware Distillation for Model Aggregation in Federated Learning
S Su, B Li, X Xue
arXiv preprint arXiv:2210.02190, 2022
12022
Collaborative Chinese Text Recognition with Personalized Federated Learning
S Su, H Yu, B Li, X Xue
arXiv preprint arXiv:2305.05602, 2023
2023
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients—Supplementary materials
S Su, B Li, X Xue
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