An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series

Generic and scalable framework for automated time-series anomaly detection. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . ACM, 1939–1947

Nikolay Laptev, Saeed Amizadeh, and Ian Flint. 2015 · 1947

Earlier work this paper cites.

STL: A seasonal-trend decomposition

Robert B Cleveland, William S Cleveland, Jean E McRae, and Irma Terpenning. 1990 · 1990

Earlier work this paper cites.

LOF: identifying density-based local outliers. In ACM sigmod record , Vol. 29. ACM, 93–104

Markus M Breunig, Hans-Peter Kriegel, Raymond T Ng, and Jörg Sander. 2000 · 2000

Earlier work this paper cites.

Change-point detection in time-series data based on subspace identification. In Seventh IEEE International Conference on Data Mining (ICDM 2007) . IEEE, 559–564

Yoshinobu Kawahara, Takehisa Yairi, and Kazuo Machida. 2007 · 2007

Earlier work this paper cites.

Anomaly detection: A survey

Varun Chandola, Arindam Banerjee, and Vipin Kumar. 2009 · 2009

Cited alongside, same era.

A review on time series data mining

Tak-chung Fu. 2011 · 2011

Cited alongside, same era.

Opprentice: towards practical and automatic anomaly detection through machine learning. In Proceedings of the 2015 Internet Measurement Conference . ACM, 211–224

Dapeng Liu, Youjian Zhao, Haowen Xu, Yongqian Sun, Dan Pei, Jiao Luo, Xiaowei Jing, and Mei Feng. 2015 · 2015

Cited alongside, same era.

LSTM-based encoder-decoder for multi-sensor anomaly detection

Original

Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, and Gautam Shroff. 2016 · 2016

Cited alongside, same era.

Time series anomaly detection; detection of anomalous drops with limited features and sparse examples in noisy highly periodic data

Original

Dominique T Shipmon, Jason M Gurevitch, Paolo M Piselli, and Stephen T Edwards. 2017 · 2017

Later among the works it cites.

Transfer learning for time series classification. In 2018 IEEE International Conference on Big Data (Big Data) . IEEE, 1367–1376

Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, and Pierre-Alain Muller. 2018 · 2018

Later among the works it cites.

Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . ACM, 387–395

Kyle Hundman, Valentino Constantinou, Christopher Laporte, Ian Colwell, and Tom Soderstrom. 2018 · 2018

Later among the works it cites.

Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web applications. In Proceedings of the 2018 World Wide Web Conference on World Wide Web . International World Wide Web Conferences Steering Committee, 187–196

Haowen Xu, Wenxiao Chen, Nengwen Zhao, Zeyan Li, Jiahao Bu, Zhihan Li, Ying Liu, Youjian Zhao, Dan Pei, Yang Feng, et al · 2018