CEAR: Certified Ensemble Adversarial Robustness in DNNs 事件

CEAR: Certified Ensemble Adversarial Robustness in DNNs arXiv:2606.01437v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical applications. State-of-the-art empirical defense mechanisms improve the robustness of DNNs through the training phase, but still struggle against adaptive white-box attacks. On the other hand, certified defenses offer provable guarantees of robustn