5 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 5 cited
MORA: Improving Ensemble Robustness Evaluation with Model-Reweighing Attack
Yunrui Yu, Xitong Gao, Cheng-Zhong Xu
Adversarial attacks can deceive neural networks by adding tiny perturbations to their input data. Ensemble defenses, which are trained to minimize attack transferability among sub-…
cs.CV2021★ 1 cited
Adversarial Attacks on ML Defense Models Competition
Yinpeng Dong, Qi-An Fu, Xiao Yang +25
Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…
cs.LG2021★ 3 cited
LAFEAT: Piercing Through Adversarial Defenses with Latent Features
Yunrui Yu, Xitong Gao, Cheng-Zhong Xu
Deep convolutional neural networks are susceptible to adversarial attacks. They can be easily deceived to give an incorrect output by adding a tiny perturbation to the input. This…