2 papers
cs.LG2021
When Should You Defend Your Classifier -- A Game-theoretical Analysis of Countermeasures against Adversarial Examples
Maximilian Samsinger, Florian Merkle, Pascal Schöttle +1
Adversarial machine learning, i.e., increasing the robustness of machine learning algorithms against so-called adversarial examples, is now an established field. Yet, newly propose…
cs.LG2021
Pruning in the Face of Adversaries
Florian Merkle, Maximilian Samsinger, Pascal Schöttle
The vulnerability of deep neural networks against adversarial examples - inputs with small imperceptible perturbations - has gained a lot of attention in the research community rec…