Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression

5 February 2021

Papers citing "Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression"

7 / 7 papers shown

Title
Exploring the Relationship between Architecture and Adversarially Robust Generalization Aishan Liu Shiyu Tang Siyuan Liang Ruihao Gong Boxi Wu Xianglong Liu Dacheng Tao AAML 31 18 0 28 Sep 2022
Why Adversarial Training of ReLU Networks Is Difficult? Xu Cheng Hao Zhang Yue Xin Wen Shen Jie Ren Quanshi Zhang AAML 8 3 0 30 May 2022
Alleviating Robust Overfitting of Adversarial Training With Consistency Regularization Shudong Zhang Haichang Gao Tianwei Zhang Yunyi Zhou Zihui Wu AAML 18 3 0 24 May 2022
Smoothness Analysis of Adversarial Training Sekitoshi Kanai Masanori Yamada Hiroshi Takahashi Yuki Yamanaka Yasutoshi Ida AAML 40 6 0 02 Mar 2021
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 55 101 0 16 Oct 2019
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 264 3,110 0 04 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 284 2,890 0 15 Sep 2016