… learning algorithms along with their applications in future wireless networks are introduced,
such as Q-learning for the … in downlink femtocell networks and Bayesian learning for channel …

… learning techniques are presented. Our work discusses machine learning algorithms based
… to encourage the adoption of existing machine learning solutions in WSN applications. Lastly…

… by the integration of machine learning (ML) notions across the wireless core and edge …
networks (ANNs)-based ML algorithms can be employed for solving various wireless networking …

… learning is one of the most important data processing approaches in ML. In supervised learning,
we … A major responsibilities of supervised learning algorithms are to generate the model …

… In this article, we will introduce the basic concept of machine learning algorithms and the
corresponding applications according to the category of supervised, unsupervised, and …

… major families of machine learning algorithms and discussed their potential applications
in the context of intelligent wireless networks, in order to facilitate future networks with high-level …

… amount of network … wireless networks with many nodes and dynamic link quality. This paper
performs a comprehensive survey of the applications of DL algorithms for different network …

… reference for wireless sensor network infrastructure and the … learning algorithms by reducing
the security costs of wireless … to adapting machine learning algorithms to the capabilities of …

… deep learning and machine learning algorithms and strategies in wireless networks and find
… a system that detects, predicts and recovers from abnormal situations on wireless networks. …

… learning algorithms in solving network resource allocation problems. In future work, we
will … into the learning algorithms and design neural networks adapted to wireless networks. …