paper

Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks

arXiv:2602.10401

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.

Accepted at Optical Fiber Communications Conference 2026 (OFC 2026)

Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks · wovepaper