Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling

Anomaly detection (AD) is increasingly recognized as a key component for ensuring the resilience of future communication systems. While deep learning has shown state-of-the-art AD performance, its application in critical systems is hindered by concerns regarding training data efficiency, domain adap...

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Bibliographic Details
Main Authors: Lukas Schynol, Marius Pesavento
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10918821/
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