5 citations · 8 across the 4 of their papers we have counts for
4 papers · 1 filter
Improving Model Robustness with Latent Distribution Locally and Globally
Zhuang Qian, Shufei Zhang, Kaizhu Huang +3
In this work, we consider model robustness of deep neural networks against adversarial attacks from a global manifold perspective. Leveraging both the local and global latent infor…
Robust Generative Adversarial Network
Shufei Zhang, Zhuang Qian, Kaizhu Huang +2
Generative adversarial networks (GANs) are powerful generative models, but usually suffer from instability and generalization problem which may lead to poor generations. Most exist…
On Model Robustness Against Adversarial Examples
Shufei Zhang, Kaizhu Huang, Zenglin Xu
We study the model robustness against adversarial examples, referred to as small perturbed input data that may however fool many state-of-the-art deep learning models. Unlike previ…
Manifold Adversarial Learning
Shufei Zhang, Kaizhu Huang, Jianke Zhu +1
Recently proposed adversarial training methods show the robustness to both adversarial and original examples and achieve state-of-the-art results in supervised and semi-supervised…