Yan Sun
Yan Sun
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Cited by
Fedspeed: Larger local interval, less communication round, and higher generalization accuracy
Y Sun, L Shen, T Huang, L Ding, D Tao
The 11th International Conference on Learning Representations (ICLR 2023), 2023
Improving the model consistency of decentralized federated learning
Y Shi, L Shen, K Wei, Y Sun, B Yuan, X Wang, D Tao
The 40th International Conference on Machine Learning (ICML 2023), 2023
On efficient training of large-scale deep learning models: A literature review
L Shen, Y Sun, Z Yu, L Ding, X Tian, D Tao
arXiv preprint arXiv:2304.03589, 2023
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
Y Sun, L Shen, S Chen, L Ding, D Tao
The 40th International Conference on Machine Learning (ICML 2023), 2023
Visual Prompt Based Personalized Federated Learning
G Li, W Wu, Y Sun, L Shen, B Wu, D Tao
Transactions on Machine Learning Research (TMLR), 2023
Subspace based federated unlearning
G Li, L Shen, Y Sun, Y Hu, H Hu, D Tao
arXiv preprint arXiv:2302.12448, 2023
Fusion of Global and Local Knowledge for Personalized Federated Learning
T Huang, L Shen, Y Sun, W Lin, D Tao
Transactions on Machine Learning Research (TMLR), 2023
Efficient federated prompt tuning for black-box large pre-trained models
Z Lin, Y Sun, Y Shi, X Wang, L Huang, L Shen, D Tao
arXiv preprint arXiv:2310.03123, 2023
Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup
Y Sun, L Shen, H Sun, L Ding, D Tao
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization
Y Sun, L Shen, D Tao
The 37th Conference on Neural Information Processing Systems (NIPS 2023), 2023
FedGAMMA: Federated Learning With Global Sharpness-Aware Minimization
R Dai, X Yang, Y Sun, L Shen, X Tian, M Wang, Y Zhang
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Towards more suitable personalization in federated learning via decentralized partial model training
Y Shi, Y Liu, Y Sun, Z Lin, L Shen, X Wang, D Tao
arXiv preprint arXiv:2305.15157, 2023
Enhance local consistency in federated learning: A multi-step inertial momentum approach
Y Liu, Y Sun, Z Ding, L Shen, B Liu, D Tao
arXiv preprint arXiv:2302.05726, 2023
Which mode is better for federated learning? Centralized or Decentralized
Y Sun, L Shen, D Tao
arXiv preprint arXiv:2310.03461, 2023
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