On the Loss Landscape of Adversarial Training: Identifying Challenges
and How to Overcome Them

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

15 June 2020

Mathieu Salzmann

Sabine Süsstrunk

Papers citing "On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them"

18 / 18 papers shown

Title
Uniformly Stable Algorithms for Adversarial Training and Beyond Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 48 0 0 03 May 2024
Effective Gradient Sample Size via Variation Estimation for Accelerating Sharpness aware Minimization Jiaxin Deng Junbiao Pang Baochang Zhang Tian Wang 48 1 0 24 Feb 2024
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead Marlon Becker Frederick Altrock Benjamin Risse 79 5 0 22 Jan 2024
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 32 30 0 03 Oct 2022
Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis Jiancong Xiao Zeyu Qin Yanbo Fan Baoyuan Wu Jue Wang Zhimin Luo AAML 31 7 0 02 Oct 2022
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization Xiaotian Han Tong Zhao Yozen Liu Xia Hu Neil Shah GNN 55 36 0 30 Sep 2022
Boosting Factorization Machines via Saliency-Guided Mixup Chenwang Wu Defu Lian Yong Ge Min Zhou Enhong Chen Dacheng Tao 13 4 0 17 Jun 2022
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations? Alvin Chan Yew-Soon Ong Clement Tan AAML 24 13 0 09 May 2022
Defending Black-box Skeleton-based Human Activity Classifiers He-Nan Wang Yunfeng Diao Zichang Tan G. Guo AAML 51 10 0 09 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 13 18 0 03 Mar 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 29 4 0 03 Feb 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 23 13 0 14 Dec 2021
Location Leakage in Federated Signal Maps Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 20 5 0 07 Dec 2021
Sharpness-aware Quantization for Deep Neural Networks Jing Liu Jianfei Cai Bohan Zhuang MQ 27 24 0 24 Nov 2021
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars Chun Tao Deboleena Roy I. Chakraborty Kaushik Roy AAML 26 2 0 19 Sep 2021
Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression Masanori Yamada Sekitoshi Kanai Tomoharu Iwata Tomokatsu Takahashi Yuki Yamanaka Hiroshi Takahashi Atsutoshi Kumagai AAML 16 9 0 05 Feb 2021
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 308 2,890 0 15 Sep 2016