arXiv · 2602.10401
Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks
Abstract
We present a novel online learning-based approach for concept drift adaptation in optical network failure detection, achieving up to a 70% improvement in performance over conventional static models while maintaining low latency.
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Yousuf Moiz Ali, Jaroslaw E. Prilepsky, João Pedro, Antonio Napoli, Sasipim Srivallapanondh, Sergei K. Turitsyn, Pedro Freire. 2026-02-11. Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks. https://arxiv.org/abs/2602.10401
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