Li Shen
Li Shen
JD Explore Academy
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Cited by
Cited by
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
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
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
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
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
S Liu, T Chen, X Chen, Z Atashgahi, L Yin, H Kou, L Shen, M Pechenizkiy, ...
NeurIPS, 2021
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
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
Z Guo, M Liu, Z Yuan, L Shen, W Liu, T Yang
ICML, 2020
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
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
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
Enhanced Balanced Min Cut
X Chen, W Hong, F Nie, JZ Huang, L Shen
International Journal of Computer Vision 128 (7), 2020
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
AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks
Y Tian, L Shen, L Shen, G Su, Z Li, W Liu
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
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
Attacking adversarial attacks as a defense
B Wu, H Pan, L Shen, J Gu, S Zhao, Z Li, D Cai, X He, W Liu
arXiv preprint arXiv:2106.04938, 2021
Quantized Adam with Error Feedback
C Chen, L Shen, H Huang, W Liu
ACM Transactions on Intelligent Systems and Technology 12 (5), 1–26, 2021
DAG-GAN: Causal structure learning with generative adversarial nets
Y Gao, L Shen, ST Xia
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2021
Discrete Trust-aware Matrix Factorization for Fast Recommendation
G Guo, E Yang, L Shen, X Yang, X He
Proceedings of the Twenty-Eighth International Joint Conference on …, 2019
Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution
H Huang, L Shen, C He, W Dong, W Liu
IEEE Transactions on Circuits and Systems for Video Technology, 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
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