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On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms

Authors:

Kenji Yamanishi,

Jun-Ichi Takeuchi,

Graham Williams,

Peter MilneAuthors Info & Claims

KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 320 - 324

https://doi.org/10.1145/347090.347160

Published: 01 August 2000 Publication History

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Cited By

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Fei KZhou JZhou YGu XFan HLi BWang WChen Y(2025)LaAeb: A comprehensive log-text analysis based approach for insider threat detectionComputers & Security10.1016/j.cose.2024.104126148(104126)Online publication date: Jan-2025
https://doi.org/10.1016/j.cose.2024.104126
Zhang CShen WWang SWu Y(2024)Network Anomaly Detection Algorithm Based on Fusion of Artificial Fish Swarming and Isolation Forest2024 5th International Conference on Computer Engineering and Application (ICCEA)10.1109/ICCEA62105.2024.10603987(238-242)Online publication date: 12-Apr-2024
https://doi.org/10.1109/ICCEA62105.2024.10603987
Phelps CLahiry AIslam TPouchard L(2024)Reimagine Application Performance as a Graph: Novel Graph-Based Method for Performance Anomaly Classification in High-Performance Computing2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC61105.2024.00041(240-245)Online publication date: 2-Jul-2024
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Index Terms

On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Information systems applications
    1. Data mining

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Published In

KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining

August 2000

537 pages

ISBN:1581132336

DOI:10.1145/347090

Chairmen:
Raghu Ramakrishnan
Univ. of Wisconsin
,
Sal Stolfo
Columbia Univ., New York, NY
,
Roberto Bayardo
IBM Almaden Research Center, San Jose, CA
,
Ismail Parsa
Epsilon

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2000

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KDD00

Sponsor:

KDD00: The Second Annual International Conference on Knowledge Discovery in Data

August 20 - 23, 2000

Massachusetts, Boston, USA

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Fei KZhou JZhou YGu XFan HLi BWang WChen Y(2025)LaAeb: A comprehensive log-text analysis based approach for insider threat detectionComputers & Security10.1016/j.cose.2024.104126148(104126)Online publication date: Jan-2025
https://doi.org/10.1016/j.cose.2024.104126
Zhang CShen WWang SWu Y(2024)Network Anomaly Detection Algorithm Based on Fusion of Artificial Fish Swarming and Isolation Forest2024 5th International Conference on Computer Engineering and Application (ICCEA)10.1109/ICCEA62105.2024.10603987(238-242)Online publication date: 12-Apr-2024
https://doi.org/10.1109/ICCEA62105.2024.10603987
Phelps CLahiry AIslam TPouchard L(2024)Reimagine Application Performance as a Graph: Novel Graph-Based Method for Performance Anomaly Classification in High-Performance Computing2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC61105.2024.00041(240-245)Online publication date: 2-Jul-2024
https://doi.org/10.1109/COMPSAC61105.2024.00041
Chen ZZhao KSun R(2024)Multi-modal data novelty detection with adversarial autoencodersApplied Soft Computing10.1016/j.asoc.2024.112063(112063)Online publication date: Aug-2024
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Deng XYang LZhang AWang JWang HXing TXu P(2024)Synergetic proto-pull and reciprocal points for open set recognitionMachine Vision and Applications10.1007/s00138-024-01596-235:5Online publication date: 23-Aug-2024
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