Unsupervised Dictionary Learning for Anomaly Detection

Paul Irofti; Andra Băltoiu

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arXiv · 2003.00293

Unsupervised Dictionary Learning for Anomaly Detection

Paul Irofti·Andra Băltoiu

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Abstract

We investigate the possibilities of employing dictionary learning to address the requirements of most anomaly detection applications, such as absence of supervision, online formulations, low false positive rates. We present new results of our recent semi-supervised online algorithm, TODDLeR, on a anti-money laundering application. We also introduce a novel unsupervised method of using the performance of the learning algorithm as indication of the nature of the samples.

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cs.LG cs.CR cs.CV cs.NA math.NA

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Paul Irofti, Andra Băltoiu. 2020-02-29. Unsupervised Dictionary Learning for Anomaly Detection. https://arxiv.org/abs/2003.00293

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