MDGAN: Boosting Anomaly Detection Using \\Multi-Discriminator Generative Adversarial Networks

Anomaly detection is often considered a challenging field of machine learning due to the difficulty of obtaining anomalous samples for training and the need to obtain a sufficient amount of training data. In recent years, autoencoders have been shown to be effective anomaly detectors that train only...

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Hauptverfasser:	Intrator, Yotam, Katz, Gilad, Shabtai, Asaf
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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