Sergei K. Turitsyn

Yousuf Moiz Ali, Jaroslaw E. Prilepsky, João Pedro et al.

We propose a hybrid active-online learning framework for label-efficient concept drift adaptation in optical network failure detection. Using margin-based selective labeling, our method achieves nearceiling accuracy and AUC scores while querying only 3.4% of streaming samples, with negligible latency overhead compared to static inference.