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ORCIDShangchao Su
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2020 – today
- 2025
[c7]Tiandi Ye
, Wenyan Liu, Kai Yao, Lichun Li, Shangchao Su, Cen Chen, Xiang Li, Shan Yin, Ming Gao:
Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning. CIKM 2025: 3877-3887- [c6]Mingzhao Yang, Shangchao Su, Bin Li, Xiangyang Xue:
One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models. ICML 2025 - [i12]Tiandi Ye, Wenyan Liu, Kai Yao, Lichun Li, Shangchao Su, Cen Chen, Xiang Li, Shan Yin, Ming Gao:
Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning. CoRR abs/2508.19621 (2025) - [i11]Lu Zhao, Rong Shi, Shaoqing Zhang, Shangchao Su, Ziqing Yin, Zhiyan Cui, Hongfeng Sun, Baoguo He, Yueqiang Chen, Liang Dong, Xiyuan Li, Lingbin Wang, Lijun Ma, Qiang Huang, Ting Liu, Chong Wang, Can Wei:
MoFa: A Unified Performance Modeling Framework for LLM Pretraining. CoRR abs/2511.09837 (2025) - [i10]Lu Zhao, Rong Shi, Yue Sun, Shaoqing Zhang, Hongxing Niu, Yueqiang Chen, Baoguo He, Hongfeng Sun, Ziqing Yin, Shangchao Su, Zhiyan Cui, Liang Dong, Xiyuan Li, Lingbin Wang, Jianwei He, Jiesong Ma, Weikang Huang, Jianglei Tong, Dongdong Gao, Jian Zhang, Hong Tian, Zhaoqun Sun, Hui Shen:
MemFine: Memory-Aware Fine-Grained Scheduling for MoE Training. CoRR abs/2511.21431 (2025) - 2024
- [c5]Shangchao Su, Mingzhao Yang, Bin Li, Xiangyang Xue:
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning. AAAI 2024: 15117-15125 - [c4]Mingzhao Yang, Shangchao Su, Bin Li, Xiangyang Xue:
Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models. AAAI 2024: 16325-16333 - [c3]Shangchao Su, Bin Li, Xiangyang Xue:
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients. ECCV (48) 2024: 342-358 - [c2]Mingzhao Yang, Shangchao Su, Bin Li, Xiangyang Xue:
FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models. ACM Multimedia 2024: 6666-6675 - [i9]Mingzhao Yang, Shangchao Su, Bin Li, Xiangyang Xue:
FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models. CoRR abs/2407.19953 (2024) - 2023
- [j1]Shangchao Su, Bin Li, Xiangyang Xue:
One-shot Federated Learning without server-side training. Neural Networks 164: 203-215 (2023) - [c1]Shangchao Su, Bin Li, Chengzhi Zhang, Mingzhao Yang, Xiangyang Xue:
Cross-domain Federated Object Detection. ICME 2023: 1469-1474 - [i8]Mingzhao Yang, Shangchao Su, Bin Li, Xiangyang Xue:
Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model. CoRR abs/2305.04063 (2023) - [i7]Shangchao Su, Haiyang Yu, Bin Li, Xiangyang Xue:
Privacy-Preserving Collaborative Chinese Text Recognition with Federated Learning. CoRR abs/2305.05602 (2023) - [i6]Mingzhao Yang, Shangchao Su, Bin Li, Xiangyang Xue:
One-Shot Federated Learning with Classifier-Guided Diffusion Models. CoRR abs/2311.08870 (2023) - [i5]Shangchao Su, Bin Li, Xiangyang Xue:
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients. CoRR abs/2311.11227 (2023) - 2022
- [i4]Shangchao Su, Bin Li, Xiangyang Xue:
One-shot Federated Learning without Server-side Training. CoRR abs/2204.12493 (2022) - [i3]Shangchao Su, Bin Li, Chengzhi Zhang, Mingzhao Yang, Xiangyang Xue:
Cross-domain Federated Object Detection. CoRR abs/2206.14996 (2022) - [i2]Shangchao Su, Bin Li, Xiangyang Xue:
Domain Discrepancy Aware Distillation for Model Aggregation in Federated Learning. CoRR abs/2210.02190 (2022) - [i1]Shangchao Su, Mingzhao Yang, Bin Li, Xiangyang Xue:
Cross-domain Federated Adaptive Prompt Tuning for CLIP. CoRR abs/2211.07864 (2022)
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