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Boosting Fast Adversarial Training With Learnable Adversarial Initialization

IEEE Transactions on Image Processing, 2022
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Xiaojun Jia, Yong Zhang, Baoyuan Wu
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Adversarial Training With Anti-Adversaries

IEEE Transactions on Pattern Analysis and Machine Intelligence
Adversarial training is effective in improving the robustness of deep neural networks. However, existing studies still exhibit significant drawbacks in terms of the robustness, generalization, and fairness of models. In this study, we validate the importance of different perturbation directions (i.e., adversarial and anti-adversarial) and bounds from ...
Xiaoling Zhou, Ou Wu, Nan Yang
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Adversarial Training with Orthogonal Regularization

2020 28th Signal Processing and Communications Applications Conference (SIU), 2020
Deep neural networks have been successful in various domains, such as computer vision and natural language processing. On the other hand, researchers have discovered a vulnerability of convolutional neural networks to the samples with imperceptible perturbations, also known as, adversarial perturbations.
Oguz Kaan Yüksel, Inci Meliha Baytas
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Optimal training for adversarial games

Annals of Mathematics and Artificial Intelligence, 2021
In this paper, adversarial games that have an associated differential system induced by a Hamiltonian function are solved using a continuous version of the simultaneous gradient descent method. As Nash equilibrium is not always reached by that method, optimal training times are discussed as well.
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Deep Recommendation With Adversarial Training

IEEE Transactions on Emerging Topics in Computing, 2022
Chenyan Zhang +5 more
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A Survey on Generative Adversarial Networks: Variants, Applications, and Training

ACM Computing Surveys, 2022
Xi Li
exaly

Boosting adversarial robustness via self-paced adversarial training

Neural Networks, 2023
Lirong He, Qingzhong Ai, Xincheng Yang +2 more
exaly

Fast Adversarial Training With Adaptive Step Size

IEEE Transactions on Image Processing, 2023
Zhichao Huang, Yanbo Fan, Chen Liu
exaly

A New Perspective on Stabilizing GANs Training: Direct Adversarial Training

IEEE Transactions on Emerging Topics in Computational Intelligence, 2023
Ziqiang Li, Pengfei Xia, Rentuo Tao
exaly

adversarial attacks
deep learning
robustness

adversarial robustness
adversarial attack
adversarial examples

data augmentation
deep neural network
adversarial machine learning