… of Wireless Sensor Networks (WSNs), Machine Learning (ML… or problems of the sensors
networks and the ML techniques. … Furthermore, we also consider the concept of Deep Learning …

Machine learning (ML) technology has shown its unique advantages in many fields and has
excellent performance in many applications, such as image recognition, speech recognition, …

… to deploying machine learning predictors in practice for wireless network optimization and …
discussion on machine learning methods to realistic applications in mobile wireless networks. …

… communications and adversarial machine learning, they are … depth discussions of AML in
wireless communications. However, … of wireless signal model, the deep neural network and the …

… , which is based on machine learning techniques to obtain both the position information
of users and the trajectory design of UAVs. First, a multi-agent Q-learning-based placement …

… , machine learning (ML) approaches have been invoked in UAV-enabled wireless networks.
… Optimizing the precoding matrix by machine learning algorithms will be considered in our …

… network, which is not scalable for the more practical, congested scenarios. The main
contribution of this paper is a novel machine learning … to provide aerial wireless service to mobile …

… also enables the wireless network service providers to (i) offer … network edge, (ii) implement
application-based traffic steering across the access networks, (iii) enable dynamic network …

… machine learning approaches in the wireless area; Section 3: we introduce and summarize
state-of-the-art attack on machine learning … -art adversarial machine learning over wireless …

… machine learning approaches in physical layer authentication models increased wireless
network … in using machine learning (ML) and deep learning (DL) approaches for PLA in …