DeepAD: A Generic Framework Based on Deep Learning for Time Series Anomaly Detection

Teodora Sandra Buda, Bora Caglayan, Haytham Assem. DeepAD: A Generic Framework Based on Deep Learning for Time Series Anomaly Detection. In Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi, editors, Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part I. Volume 10937 of Lecture Notes in Computer Science, pages 577-588, Springer, 2018. [doi]

Abstract

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