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Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks

机译：双侧对抗培训：对对抗对抗攻击更强大的模型进行快速培训

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Jianyu Wang; Haichao Zhang;
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1. Robust Graph Neural Networks Against Adversarial Attacks via Jointly Adversarial Training [J] . Hu Tian, Bowei Ye, Xiaolong Zheng, IFAC PapersOnLine . 2020,第5期

机译：通过共同对抗培训，强大的图形神经网络对抗对抗攻击
2. Addressing The False Negative Problem of Deep Learning MRI Reconstruction Models by Adversarial Attacks and Robust Training [J] . Kaiyang Cheng, Francesco Calivá, Rutwik Shah, JMLR: Workshop and Conference Proceedings . 2020,第2010期

机译：通过对抗攻击和强大的培训来解决深度学习MRI重建模型的假阴性问题
3. Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training [J] . Xi Wu, Uyeong Jang, Jiefeng Chen, JMLR: Workshop and Conference Proceedings . 2018,第3期

机译：利用对抗训练产生的模型置信度增强对抗鲁棒性
4. Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks [C] . Jianyu Wang, Haichao Zhang International Conference on Computer Vision . 2019

机译：双边对抗训练：旨在快速训练更强大的对抗对抗攻击的模型
5. Robust and Generalizable Machine Learning Through Generative Models,Adversarial Training, and Physics Priors [D] . Yao, Houpu. 2019

机译：通过生成模型，对抗性训练和物理前瞻学习鲁棒和更广泛的机器
6. Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative adversarial networks [O] . Atsushi Teramoto, Tetsuya Tsukamoto, Ayumi Yamada, 2020

机译：深层学习方法肺细胞学图像分类：使用实际和合成图像的两步训练通过逐步生长的生长生长育种网络
7. Diversity Adversarial Training against Adversarial Attack on Deep Neural Networks [O] . Hyun Kwon, Jun Lee 2021

机译：深度神经网络对抗对抗攻击的多样性对抗培训

Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks

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