@inproceedings{90dd1fb9ebb645e2a0dcac95e46562d8,
title = "Machine Learning-Driven Low-Complexity Optical Power Optimization for Point-to-Point Links",
abstract = "We propose a strategy to dynamically adjust transmitted power solely based on the analysis of performance fluctuations due to polarization-dependent loss. We show that our method converges faster to optimum compared to a standard approach.",
author = "Isaia Andrenacci and Matteo Lonardi and Petros Ramantanis and {\'E}lie Awwad and Ekhi{\~n}e Irurozki and Stephan Cl{\'e}men{\c c}on and Paolo Serena and Chiara Lasagni and S{\'e}bastien Bigo and Patricia Layec",
note = "Publisher Copyright: {\textcopyright} 2024 The Author(s).; 2024 Optical Fiber Communication Conference, OFC 2024 ; Conference date: 24-03-2024 Through 28-03-2024",
year = "2024",
language = "English",
series = "Optical Fiber Communication Conference in Proceedings Optical Fiber Communication Conference, OFC 2024",
publisher = "Optical Society of America",
booktitle = "Optical Fiber Communication Conference in Proceedings Optical Fiber Communication Conference, OFC 2024",
}