Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 9 references that are in the map. First posted on arXiv 11 Feb 2026.
Builds on
2 of 9 references.
References · 2
- 2020Learning under Concept Drift: A Reviewcited by 477
- 2018Online Learning: A Comprehensive Surveycited by 205
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Citing papers per year: 2026: 1.
1 paper.