| Fedml: A research library and benchmark for federated machine learning C He, S Li, J So, X Zeng, M Zhang, H Wang, X Wang, P Vepakomma, ... arXiv preprint arXiv:2007.13518, 2020 | 673* | 2020 |
| A sufficient condition for convergences of adam and rmsprop F Zou*, L Shen*, Z Jie, W Zhang, W Liu IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 11127 …, 2019 | 522 | 2019 |
| Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning L Zhang, L Shen, L Ding, D Tao, L Duan IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 324 | 2022 |
| Towards Making the Most of ChatGPT for Machine Translation K Peng, L Ding, Q Zhong, L Shen, X Liu, M Zhang, Y Ouyang, D Tao The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023 | 282 | 2023 |
| DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training R Dai, L Shen, F He, X Tian, D Tao The 39th International Conference on Machine Learning (ICML), 2022 | 143 | 2022 |
| Sparse Training via Boosting Pruning Plasticity with Neuroregeneration S Liu, T Chen, X Chen, Z Atashgahi, L Yin, H Kou, L Shen, M Pechenizkiy, ... The Thirty-Fifth Annual Conference on Neural Information Processing Systems …, 2021 | 130 | 2021 |
| The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training S Liu, T Chen, X Chen, L Shen, DC Mocanu, Z Wang, M Pechenizkiy The Tenth International Conference on Learning Representations (ICLR), 2022 | 120 | 2022 |
| Stochastic Client Selection for Federated Learning with Volatile Clients T Huang, W Lin, L Shen, K Li, AY Zomaya IEEE Internet of Things Journal, 2022 | 117 | 2022 |
| A Unified Analysis of AdaGrad with Weighted Aggregation and Momentum Acceleration L Shen, C Chen, F Zou, Z Jie, J Sun, W Liu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 104* | 2023 |
| Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning S Fu, F He, Y Liu, L Shen, D Tao The Tenth International Conference on Learning Representations (ICLR), 2022 | 87* | 2022 |
| Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation Z Qin, Y Fan, Y Liu, L Shen, Y Zhang, J Wang, B Wu The Thirty-Sixth Annual Conference on Neural Information Processing Systems …, 2022 | 81 | 2022 |
| Fedcv: a federated learning framework for diverse computer vision tasks C He, AD Shah, Z Tang, DFAN Sivashunmugam, K Bhogaraju, M Shimpi, ... arXiv preprint arXiv:2111.11066, 2021 | 81 | 2021 |
| AdaMerging: Adaptive Model Merging for Multi-Task Learning E Yang, Z Wang, L Shen, S Liu, G Guo, X Wang, D Tao The Twelfth International Conference on Learning Representations (ICLR), 2024 | 72 | 2024 |
| Understanding Robust Overfitting of Adversarial Training and Beyond C Yu, B Han, L Shen, J Yu, C Gong, M Gong, T liu The 39th International Conference on Machine Learning (ICML), 2022 | 72 | 2022 |
| Penalized Proximal Policy Optimization for Safe Reinforcement Learning L Zhang, L Shen, L Yang, S Chen, B Yuan, X Wang, D Tao The 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022 | 70 | 2022 |
| Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach P Mi, L Shen, T Ren, Y Zhou, X Sun, R Ji, D Tao The Thirty-Sixth Annual Conference on Neural Information Processing Systems …, 2022 | 65 | 2022 |
| Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning C Liu, C Lou, R Wang, AY Xi, L Shen, J Yan The 39th International Conference on Machine Learning (ICML), 2022 | 64 | 2022 |
| Make Landscape Flatter in Differentially Private Federated Learning Y Shi, Y Liu, K Wei, L Shen, X Wang, D Tao IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 59 | 2023 |
| Deep Model Fusion: A Survey W Li, Y Peng, M Zhang, L Ding, H Hu, L Shen arXiv preprint arXiv:2309.15698, 2023 | 54 | 2023 |
| Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models Q Zhong, L Ding, L Shen, P Mi, J Liu, B Du, D Tao Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 54 | 2022 |
Dacheng TaoNanyang Technological University在 ntu.edu.sg 的电子邮件经过验证
