Ensemble Outlier Detection
Ensemble Outlier Detection is an outlier detection paradigm that combines multiple base outlier detection models to improve detection accuracy and robustness by leveraging the strengths of diverse individual detectors through aggregation strategies.
109
Publications
5.9K
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358
Authors
183
Institutions
Publications per year
2017–2026
83
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109
Progress in Outlier Detection Techniques: A Survey
Hongzhi Wang, Mohamed Jaward Bah, Mohamed Hammad · IEEE Access · 2019 · 508 citations · Full text
Interpreting and Unifying Outlier Scores
Hans‐Peter Kriegel, Peer Kröger, Erich Schubert et al. · 2011 · 270 citations
Computing, Data Science, Data Mining +16
Outlier Detection for Time Series with Recurrent Autoencoder Ensembles
Tung Kieu, Bin Yang, Chenjuan Guo et al. · 2019 · 268 citations · Full text
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183

University of Alberta
Edmonton, Canada
4 h-index
8 publications
1.1K citations

National University of Defense Technology
Changsha, China
4 h-index
15 publications
335 citations

University of Toronto
Toronto, Canada
4 h-index
6 publications
105 citations

Northeastern University
Shenyang, China
4 h-index
5 publications
186 citations
Ludwig-Maximilians-Universität München
Munich, Germany
4 h-index
10 publications
2K citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
5 publications
287 citations
Michigan State University
East Lansing, United States
3 h-index
7 publications
516 citations

École de Technologie Supérieure
Montreal, Canada
3 h-index
7 publications
241 citations
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Repository · 7 publications · 175 citations
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6 publications · 252 citations
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3 publications · 145 citations
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3 publications · 210 citations
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3 publications · 596 citations
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