| Arbitrary style transfer with deep feature reshuffle S Gu, C Chen, J Liao, L Yuan Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 189 | 2018 |
| Adam can converge without any modification on update rules Y Zhang, C Chen, N Shi, R Sun, ZQ Luo Advances in neural information processing systems 35, 28386-28399, 2022 | 39 | 2022 |
| Quantized adam with error feedback C Chen, L Shen, H Huang, W Liu ACM Transactions on Intelligent Systems and Technology (TIST) 12 (5), 1-26, 2021 | 28 | 2021 |
| Towards practical adam: Non-convexity, convergence theory, and mini-batch acceleration C Chen, L Shen, F Zou, W Liu Journal of Machine Learning Research 23 (229), 1-47, 2022 | 18 | 2022 |
| Communication efficient primal-dual algorithm for nonconvex nonsmooth distributed optimization C Chen, J Zhang, L Shen, P Zhao, Z Luo International Conference on Artificial Intelligence and Statistics, 1594-1602, 2021 | 14 | 2021 |
| Efficient-Adam: Communication-efficient distributed Adam with complexity analysis C Chen, L Shen, W Liu, ZQ Luo arXiv preprint arXiv:2205.14473, 2022 | 9 | 2022 |
| A semi-automatic editing method for surgery videos Z Fan, C Chen, T Jiang 2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW …, 2017 | 4 | 2017 |
| Efficient-Adam: Communication-Efficient Distributed Adam C Chen, L Shen, W Liu, ZQ Luo IEEE Transactions on Signal Processing, 2023 | | 2023 |
