With the rapid development of Internet and communication systems, both in the aspect of
services and technologies, communication networks have been suffering increasing …

Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Machine learning (ML) has disrupted a wide range of science and engineering disciplines in
recent years. ML applications in optical communications and networking are also gaining …

Artificial intelligence (AI) is an extensive scientific discipline which enables computer
systems to solve problems by emulating complex biological processes such as learning …

With the rapid development of optical communication systems, more advanced techniques
conventionally used in long-haul transmissions have gradually entered systems covering …

Failure management plays a significant role in optical networks. It ensures secure operation,
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …

Techniques from artificial intelligence have been widely applied in optical communication
and networks, evolving from early machine learning (ML) to the recent deep learning (DL) …

In the optical networks, the dynamicity, the complexity and the heterogeneity have
dramatically increased owing to the deployment of advanced coherent techniques, and the …

Recently, machine learning (ML) has attracted the attention of both researchers and
practitioners to address several issues in the optical networking field. This trend has been …

Networks are complex interacting systems involving cloud operations, core and metro
transport, and mobile connectivity all the way to video streaming and similar user …