Anomaly detection

Results: 503



#Item
41Charu C. Aggarwal IBM T J Watson Research Center Yorktown, NYOutlier Ensembles

Charu C. Aggarwal IBM T J Watson Research Center Yorktown, NYOutlier Ensembles

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Source URL: www.outlier-analytics.org

Language: English - Date: 2013-08-13 03:47:38
42Visualizing Anomalies in Sensor Networks Qi Liao∗ , Lei Shi† , Yuan He‡ , Rui Li§ , Zhong Su† , Aaron Striegel∗ , Yunhao Liu ∗ University of Notre Dame, USA. E-mail: {qliao,striegel}@nd.edu. † IBM Researc

Visualizing Anomalies in Sensor Networks Qi Liao∗ , Lei Shi† , Yuan He‡ , Rui Li§ , Zhong Su† , Aaron Striegel∗ , Yunhao Liu ∗ University of Notre Dame, USA. E-mail: {qliao,striegel}@nd.edu. † IBM Researc

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Source URL: conferences.sigcomm.org

Language: English - Date: 2011-08-01 22:53:42
43Paper Title (use style: paper title)

Paper Title (use style: paper title)

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Source URL: www.ridgetopgroup.com

Language: English - Date: 2015-11-09 19:14:46
44arXiv:1602.07807v2 [cs.DB] 11 AprData Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection Michael Bloodgood

arXiv:1602.07807v2 [cs.DB] 11 AprData Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection Michael Bloodgood

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Source URL: arxiv.org

Language: English - Date: 2016-04-11 20:45:58
45ISSN No: International Journal & Magazine of Engineering, Technology, Management and Research A Monthly Peer Reviewed Open Access International e-Journal

ISSN No: International Journal & Magazine of Engineering, Technology, Management and Research A Monthly Peer Reviewed Open Access International e-Journal

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Source URL: www.ijmetmr.com

Language: English - Date: 2014-12-12 08:36:52
46Enhancing One-class Support Vector Machines for Unsupervised Anomaly Detection Mennatallah Amer1, Markus Goldstein2, Slim Abdennadher1 1  2

Enhancing One-class Support Vector Machines for Unsupervised Anomaly Detection Mennatallah Amer1, Markus Goldstein2, Slim Abdennadher1 1 2

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Source URL: www.outlier-analytics.org

Language: English - Date: 2013-08-13 15:59:38
47Latent Outlier Detection and the Low Precision Problem Fei Wang Sanjay Chawla  Didi Surian

Latent Outlier Detection and the Low Precision Problem Fei Wang Sanjay Chawla Didi Surian

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Source URL: www.outlier-analytics.org

Language: English - Date: 2013-07-04 03:56:20
48Anomaly detection from server log data.  A case study

Anomaly detection from server log data. A case study

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Source URL: www.vtt.fi

Language: English - Date: 2015-03-18 09:57:49
49Root Cause Detection in a Service-Oriented Architecture ∗ Myunghwan Kim  Stanford University

Root Cause Detection in a Service-Oriented Architecture ∗ Myunghwan Kim Stanford University

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Source URL: i.stanford.edu

Language: English - Date: 2013-08-25 23:54:25
50The Frog-Boiling Attack: Limitations of Anomaly Detection for Secure Network Coordinate Systems Eric Chan-Tin, Daniel Feldman, Nicholas Hopper, Yongdae Kim {dchantin, feldman, hopper, kyd}@cs.umn.edu University of Minnes

The Frog-Boiling Attack: Limitations of Anomaly Detection for Secure Network Coordinate Systems Eric Chan-Tin, Daniel Feldman, Nicholas Hopper, Yongdae Kim {dchantin, feldman, hopper, kyd}@cs.umn.edu University of Minnes

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Source URL: www.cs.okstate.edu

Language: English - Date: 2011-08-15 19:32:40