Deep Quantile Regression for Unsupervised Anomaly Detection in Time-Series

Deep Quantile Regression for Unsupervised Anomaly Detection in Time-Series

Yes === Time-series anomaly detection receives increasing research interest given the growing number of data-rich application domains. Recent additions to anomaly detection methods in research literature include deep neural networks (DNNs: e.g., RNN, CNN, and Autoencoder). The nature and performance...

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Bibliographic Details
Main Authors: Tambuwal, Ahmad I., Neague, Daniel
Language:en
Published: Springer 2021
Subjects:
Time-series
Anomaly detection
Prediction interval
Deep neural networks
Long short-term memory
Quantile regression
Online Access:http://hdl.handle.net/10454/18658

Internet

http://hdl.handle.net/10454/18658

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