Understanding and Improving Ensemble Adversarial Defense

27 October 2023

Papers citing "Understanding and Improving Ensemble Adversarial Defense"

10 / 10 papers shown

Title
Lightweight Defense Against Adversarial Attacks in Time Series Classification Yi Han AAML 40 0 0 04 May 2025
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models Yoojin Jung Byung Cheol Song AAML VLM MQ 36 0 0 07 Apr 2025
Adversarial Training: A Survey Mengnan Zhao Lihe Zhang Jingwen Ye Huchuan Lu Baocai Yin Xinchao Wang AAML 28 0 0 19 Oct 2024
Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective Jonghyun Park Juyeop Kim Jong-Seok Lee 23 1 0 05 Oct 2024
Hidden Activations Are Not Enough: A General Approach to Neural Network Predictions Samuel Leblanc Aiky Rasolomanana Marco Armenta 32 0 0 20 Sep 2024
Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack Zhibo Jin Jiayu Zhang Zhiyu Zhu Chenyu Zhang Jiahao Huang Jianlong Zhou Fang Chen AAML 43 1 0 14 Aug 2024
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 24 0 0 18 Nov 2022
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 73 473 0 02 Feb 2021
Label Confusion Learning to Enhance Text Classification Models Biyang Guo Songqiao Han Xiao Han Hailiang Huang Ting Lu 63 67 0 09 Dec 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 228 677 0 19 Oct 2020