The purpose of this article is to introduce the readers to the emerging technologies enabled
by deep learning and to review the research work conducted in this area that is of direct …

Abstract The Internet of Things (IoT) is expected to require more effective and efficient
wireless communications than ever before. For this reason, techniques such as spectrum …

To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Because the choice and tuning of the optimizer affects the speed, and ultimately the
performance of deep learning, there is significant past and recent research in this area. Yet …

Next-generation wireless networks must support ultra-reliable, low-latency communication
and intelligently manage a massive number of Internet of Things (IoT) devices in real-time …

This paper aims to provide a comprehensive survey of the reinforcement learning algorithms
given in the literature. Especially model-free reinforcement learning algorithms are given in …

The desire to make applications and machines more intelligent and the aspiration to enable
their operation without human interaction have been driving innovations in neural networks …

The concept of hierarchical federated edge learning (H-FEEL) has been recently proposed
as an enhancement of federated learning model. Such a system generally consists of three …

Optimization approaches in machine learning (ML) are essential for training models to
obtain high performance across numerous domains. The article provides a comprehensive …

In this paper, a novel evolutionary optimization algorithm, named Partial Reinforcement
Optimizer (PRO), is introduced. The major idea behind the PRO comes from a psychological …