3 accepted papers
Deep Neural Networks are being extensively used in communication systems and Automatic Modulation Classification (AMC) in particular. However, they are very susceptible to small adversarial perturbations that are carefully crafted to change the network decision. In this work, we build on knowledge d…
Current state of the art algorithms for recommender systems are mainly based on collaborative filtering, which exploits user ratings to discover latent factors in the data. These algorithms unfortunately do not make effective use of other features, which can help solve two well identified problems o…
The first step in solving a classification problem is to collect and label a sufficient amount of training data. Given the time and cost associated to data labeling, crowdsourcing systems (e.g., Amazon Mechanical Turk) are often used. However, one of the key disadvantages of crowdsourcing systems is…