Sparse Gaussian markov random field mixtures for anomaly detection

Tsuyoshi Idé; Ankush Khandelwal; Jayant Kalagnanam

doi:10.1109/ICDM.2016.0119

Sparse Gaussian markov random field mixtures for anomaly detection

Tsuyoshi Idé
, Ankush Khandelwal
, Jayant Kalagnanam

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

22 Scopus citations

Abstract

We propose a new approach to anomaly detection from multivariate noisy sensor data. We address two major challenges: To provide variable-wise diagnostic information and to automatically handle multiple operational modes. Our task is a practical extension of traditional outlier detection, which is to compute a single scalar for each sample. To consistently define the variable-wise anomaly score, we leverage a predictive conditional distribution. We then introduce a mixture of Gaussian Markov random field and its Bayesian inference, resulting in a sparse mixture of sparse graphical models. Our anomaly detection method is capable of automatically handling multiple operational modes while removing unwanted nuisance variables.We demonstrate the utility of our approach using real equipment data from the oil industry.

Original language	English (US)
Title of host publication	Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016
Editors	Francesco Bonchi, Josep Domingo-Ferrer, Ricardo Baeza-Yates, Zhi-Hua Zhou, Xindong Wu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	955-960
Number of pages	6
ISBN (Electronic)	9781509054725
DOIs	https://doi.org/10.1109/ICDM.2016.0119
State	Published - Jul 2 2016
Externally published	Yes
Event	16th IEEE International Conference on Data Mining, ICDM 2016 - Barcelona, Catalonia, Spain Duration: Dec 12 2016 → Dec 15 2016

Publication series

Name	Proceedings - IEEE International Conference on Data Mining, ICDM
Volume	0
ISSN (Electronic)	2374-8486

Other

Other	16th IEEE International Conference on Data Mining, ICDM 2016
Country/Territory	Spain
City	Barcelona, Catalonia
Period	12/12/16 → 12/15/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Publisher link

10.1109/ICDM.2016.0119

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Idé, T., Khandelwal, A., & Kalagnanam, J. (2016). Sparse Gaussian markov random field mixtures for anomaly detection. In F. Bonchi, J. Domingo-Ferrer, R. Baeza-Yates, Z.-H. Zhou, & X. Wu (Eds.), Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016 (pp. 955-960). Article 7837932 (Proceedings - IEEE International Conference on Data Mining, ICDM; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDM.2016.0119

Sparse Gaussian markov random field mixtures for anomaly detection. / Idé, Tsuyoshi; Khandelwal, Ankush; Kalagnanam, Jayant.
Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. ed. / Francesco Bonchi; Josep Domingo-Ferrer; Ricardo Baeza-Yates; Zhi-Hua Zhou; Xindong Wu. Institute of Electrical and Electronics Engineers Inc., 2016. p. 955-960 7837932 (Proceedings - IEEE International Conference on Data Mining, ICDM; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Idé, T, Khandelwal, A & Kalagnanam, J 2016, Sparse Gaussian markov random field mixtures for anomaly detection. in F Bonchi, J Domingo-Ferrer, R Baeza-Yates, Z-H Zhou & X Wu (eds), Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016., 7837932, Proceedings - IEEE International Conference on Data Mining, ICDM, vol. 0, Institute of Electrical and Electronics Engineers Inc., pp. 955-960, 16th IEEE International Conference on Data Mining, ICDM 2016, Barcelona, Catalonia, Spain, 12/12/16. https://doi.org/10.1109/ICDM.2016.0119

Idé T, Khandelwal A, Kalagnanam J. Sparse Gaussian markov random field mixtures for anomaly detection. In Bonchi F, Domingo-Ferrer J, Baeza-Yates R, Zhou ZH, Wu X, editors, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 955-960. 7837932. (Proceedings - IEEE International Conference on Data Mining, ICDM). doi: 10.1109/ICDM.2016.0119

Idé, Tsuyoshi ; Khandelwal, Ankush ; Kalagnanam, Jayant. / Sparse Gaussian markov random field mixtures for anomaly detection. Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. editor / Francesco Bonchi ; Josep Domingo-Ferrer ; Ricardo Baeza-Yates ; Zhi-Hua Zhou ; Xindong Wu. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 955-960 (Proceedings - IEEE International Conference on Data Mining, ICDM).

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Sparse Gaussian markov random field mixtures for anomaly detection

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