While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

Abstract 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 …

Recently, machine learning has been used in every possible field to leverage its amazing
power. For a long time, the networking and distributed computing system is the key …

The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

Research in large-scale networking systems has been shaped and will continue to be
guided by specific characteristics of applications and the underlying platforms and …

The application of unsupervised learning approaches, and in particular of clustering
techniques, represents a powerful exploration means for the analysis of network …

This special issue explores how emerging machine learning (ML) and artificial intelligence
(AI) algorithms can help computer networks become smarter. The final goal is to disseminate …

Given the unprecedented availability of data and computing resources, there is widespread
renewed interest in applying data-driven machine learning methods to problems for which …

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 …

Machine learning (ML) is a promising enabler for the fifth-generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can …