当前位置:
X-MOL 学术
›
IEEE Trans. Inform. Forensics Secur.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging
IEEE Transactions on Information Forensics and Security ( IF 6.3 ) Pub Date : 2024-06-27 , DOI: 10.1109/tifs.2024.3420128 Xiaojun Jia 1 , Yuefeng Chen 2 , Xiaofeng Mao 2 , Ranjie Duan 2 , Jindong Gu 3 , Rong Zhang 2 , Hui Xue 2 , Yang Liu 4 , Xiaochun Cao 5
中文翻译:
通过 LAW 重新审视和探索高效快速对抗训练:Lipschitz 正则化和自动权重平均
更新日期:2024-06-27
IEEE Transactions on Information Forensics and Security ( IF 6.3 ) Pub Date : 2024-06-27 , DOI: 10.1109/tifs.2024.3420128 Xiaojun Jia 1 , Yuefeng Chen 2 , Xiaofeng Mao 2 , Ranjie Duan 2 , Jindong Gu 3 , Rong Zhang 2 , Hui Xue 2 , Yang Liu 4 , Xiaochun Cao 5
Affiliation
中文翻译:
![](https://scdn.x-mol.com/jcss/images/paperTranslation.png)
通过 LAW 重新审视和探索高效快速对抗训练:Lipschitz 正则化和自动权重平均