3 accepted papers
In this paper, we study the adversarial robustness of deep neural networks (DNN) for classification against optimal classifiers. We look at the smallest magnitude of possible additive perturbations that can change a classifier
In this paper, we uniquely study the adversarial robustness of deep neural networks (NN) for classification tasks against that of optimal classifiers. We look at the smallest magnitude of possible additive perturbations that can change a classifier's output. We provide a matrix-theoretic explanati…
We consider distributed nullforming using an array of wireless transmitters that coordinate their transmissions to achieve destructive interference at a designated receiver. We describe the first experimental demonstration of distributed nullforming to a target receiver from an array of three distri…