… learning does not require direct supervision. In fact, the interactive learning paradigm is
capable of learning to … The disadvantage of reinforcement learning is, however, that it relies on …

… , the agent obtains the feedback in terms of rewards only by interacting with the environment
and learns on its own, which makes the reinforcement learning paradigm very useful for …

… learning framework to achieve intelligent and automatic network optimization by using machine
learning … Within ALF, we propose several potential paradigms, including automatic model …

… (FL) has recently emerged as a disruptive distributed learning paradigm that has an ability
to overcome all the aforementioned issues of the centralized learning approaches. Moreover, …

… We illustrate several key paradigms of leveraging SWIPT that provide over-the-air wireless
power … Her research interests include wireless communication and networking, resource …

… in wireless communication. This paper comprehensively surveys the recent advances of the
applications of ML in wireless communication… learning is also a promising paradigm for devel…

… network has already been motivated by a number of recent wireless networking paradigms,
… In Section IV, we discuss the use of ANNs for wireless communication along with the corre…

… critical but challenging communication paradigm designs with … , where machine learning
methods are utilized to learn the real-time … His interests include wireless communications with …

… learning through multi-layer transformations, extending across all three learning paradigms
mentioned before. As deep learning has growing number of applications in mobile an …

… used as a communication infrastructure for wireless ISPs in rural … wireless communications
among first responders in emergency situations, or backhaul services for large-scale wireless …