… In response, a new computing model called edge computing (EC) has drawn extensive at…
sights on AI, especially from a perspective of machine learning, a branch of AI that has gained …

… mobile edge server are used for collaborative computing to … the computing performance of
a mobile edge computing (MEC) … machine learning task-based device coordination computing …

… the necessary background of offloading issues in mobile edge computing. In Section 3, we
… 5 discusses machine learning-based offloading approaches in the mobile edge computing …

… for the ultradense IoT edge computing network via machine learning approaches, which is …
lowest user priority are assigned as edge computing and local computing, respectively. 3) For …

… machine learning for a multiuser mobile edge computing … problem in a distributed machine
learning way by optimizing the … , r This paper studies distributed machine learning for a mul- …

… that are relevant in the edge computing context. The common theme across these applications
is that they are complex machine learning tasks where deep learning has been shown to …

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 …

… to place additional computing devices at the edge of the … Deploying machine learning
systems on such edge computing … machine learning systems have been deployed at the edge …

… to deploy machine learning applications to edge servers … machine learning applications.
Intuitively, training and testing models can take a lot of time for large-scale machine learning …

In this article, a joint task, spectrum, and transmit power allocation problem is investigated
for a wireless network in which the base stations (BSs) are equipped with mobile-edge …