Mobile Edge Computing (MEC) is considered an essential future service for the
implementation of 5G networks and the Internet of Things, as it is the best method of delivering …

… While heuristicbased algorithms and data mining (DM) [7] have both played an important
role in AI solutions to IoT in the past decades, we mainly focus on machine learning (ML), a …

… trends for low-energy machine learning inference and training at the edge. It covers dataflow…
evolution has already resulted in a very broad landscape of customized machine learning …

… and storage resources to the edge of the network, involving a … of deploying machine learning
(ML) at the network edge to … developing and implementing machine learning algorithms that …

… an edge network. This article investigates the application of machine learning techniques for
in-network caching in edge … Thirdly, edge networks evolve with dynamic user associations, …

… machine learning, ie evolutionary computation techniques for major machine learning tasks
… , computer vision, deep learning, transfer learning, and ensemble learning. The paper also …

… Edge computing and machine learning will enable … learning is a common way of training
machine learning algorithms that can be later used in the inference stage on IoT and other edge …

Distributed edge intelligence is a disruptive research area that enables the … of machine
learning and deep learning (ML/DL) algorithms close to where data are generated. Since edge …

… Machine Learning (ML) has been enjoying an unprecedented surge in applications that
solve problems and enable automation in diverse domains. Primarily, this is due to the …

… Equally, if applications are dynamic and evolve over time, machine learning systems can
use new data to discover patterns and update their predictions, thus adapting with the …