Breakthroughs in Machine Learning (ML), including deep neural networks and the availability of powerful computing platforms, have recently received much attention as a key enabler for future 5G and beyond wireless networks. ML has become one of the key technologies to realize intelligent mobile networks, intelligent services, and intelligent internet-of-things (IoT). ML could provide many new opportunities in the way we manage and optimize mobile wireless communications and networks, and the way we manage different user services and user content.

However, the evolution towards learning-based mobile networks and communications is still in its early days, and much of the realization of the promised benefits requires thorough research and development. Fundamental questions such as where and how ML can really complement the well-established, well-tested mobile wireless communication systems still remain. In addition, adaptation of ML-based methods is likely needed to realize their full potential in the context of mobile wireless networks.

This Special Issue aims to share and discuss recent advances and future trends of machine learning in mobile Computing, and to bring academic researchers and industry developers together. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Advanced ML algorithms for mobile computing
• ML-based mobile networks design
• ML-based energy efficient communication/networking techniques
• ML-based sensor networks and IoT applications
• ML-based network resource allocation and optimization
• ML-based secure communications and networking
• ML-based computing on network edge
• Service performance optimization in mobile wireless networks