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