Despite regularizing the Jacobians of neural networks to enhance model robustness has
directly theoretical correlation with model prediction stability, a large defense performance …

When deploying pre-trained neural network models in real-world applications, model
consumers often encounter resource-constraint platforms such as mobile and smart devices …

Recently, single-step adversarial training has received high attention because it shows
robustness and efficiency. However, a phenomenon referred to as “catastrophic overfitting” …

Adversarial Training (AT) is a straight forward solution to learn robust models by augmenting
the training mini-batches with adversarial samples. Adversarial attack methods range from …

When deploying pre-trained neural network models in real-world applications, model
consumers often encounter resource-constraint platforms such as mobile and smart devices …