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3 papers
Hybrid Active-Online Learning Framework for Label-Efficient Concept Drift Adaptation in Optical Network Failure Detection
Yousuf Moiz Ali, Jaroslaw E. Prilepsky, João Pedro +4
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 m…
Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks
Yousuf Moiz Ali, Jaroslaw E. Prilepsky, João Pedro +4
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 conventio…
Knowledge Distillation Applied to Optical Channel Equalization: Solving the Parallelization Problem of Recurrent Connection
Sasipim Srivallapanondh, Pedro J. Freire, Bernhard Spinnler +4
To circumvent the non-parallelizability of recurrent neural network-based equalizers, we propose knowledge distillation to recast the RNN into a parallelizable feedforward structur…