Conference Proceedings

Deep multi-sphere support vector data description

Zahra Ghafoori, Christopher Leckie

Proceedings of the 2020 SIAM International Conference on Data Mining, SDM 2020 | Society for Industrial and Applied Mathematics | Published : 2020

Abstract

Deep learning is increasingly used for unsupervised feature extraction and anomaly detection in big datasets. Most deep learning based anomaly detection techniques separately train a neural network for feature extraction, then apply a traditional anomaly detection method on the extracted features. These hybrid techniques have achieved higher accuracy than traditional anomaly detection methods and reconstruction-error-based deep autoencoders. However, recent research demonstrates that jointly optimising the objectives of the deep network and the anomaly detection technique in a hybrid architecture substantially improves detection performance. Existing methods that use this objective assume th..

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