Make Some Noise: Reliable and Efficient Single-Step Adversarial Training

2 February 2022

Papers citing "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training"

6 / 6 papers shown

Title
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 25 1 0 02 Oct 2024
ADAPT to Robustify Prompt Tuning Vision Transformers Masih Eskandar Tooba Imtiaz Zifeng Wang Jennifer Dy VPVLM VLM AAML 31 0 0 19 Mar 2024
Catastrophic Overfitting: A Potential Blessing in Disguise Mengnan Zhao Lihe Zhang Yuqiu Kong Baocai Yin AAML 31 1 0 28 Feb 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense Ryota Iijima Sayaka Shiota Hitoshi Kiya 13 6 0 11 Feb 2024
Sharpness-Aware Graph Collaborative Filtering Huiyuan Chen Chin-Chia Michael Yeh Yujie Fan Yan Zheng Junpeng Wang Vivian Lai Mahashweta Das Hao Yang 8 5 0 18 Jul 2023
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 253 3,102 0 04 Nov 2016