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Sun. Jul 7, 2019

Mon. Jul 8, 2019

Tue. Jul 9, 2019

Wed. Jul 10, 2019

Thu. Jul 11, 2019

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Part 1

Machine Learning (ML) technologies are emerging and ubiquitously spread all over the industries including optical networks. Their applications in both optical transmission and optical networking have been widely investigated in recent years to increase fiber link capacity, reduce operational cost, optimize resource usage, and support new services. This workshop aims at discussing and clarifying the potential needs and advantages as well as limitations and risks (e.g. reliability issue caused by insufficient and/or inappropriate training) of ML-driven solutions for a number of use cases in optical transmissions and networks. This will be expected to facilitate innovation in aspects such as channel impairment compensation, end-to-end link optimization, physical layer monitoring and the autonomous control and management of future optical infrastructure.

Machine Learning for Optical Network and Transmission - Why and Where?

OECC/PSC 2019

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[WS1-2]Part 1