Anomaly Detection
Anomaly Detection is a data analysis technique within the broader domain of pattern recognition that identifies rare or deviating instances in a dataset whose features significantly diverge from a defined norm, thereby distinguishing them from typical or expected patterns.
13.8K
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885.3K
Citations
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2017–2026
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Robust Regression and Outlier Detection
Gregory F. Piepel, Peter J. Rousseeuw, Annick M. Leroy · Technometrics · 1989 · 6.2K citations
Fei Tony Liu, Kai Ming Ting, Zhi‐Hua Zhou · 2008 · 5.6K citations
Markus Breunig, Hans‐Peter Kriegel, Raymond T. Ng et al. · ACM SIGMOD Record · 2000 · 5.2K citations
A detailed analysis of the KDD CUP 99 data set
Mahbod Tavallaee, Ebrahim Bagheri, Wei Lu et al. · 2009 · 4.8K citations · Full text
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Chinese Academy of Sciences
Beijing, China
59 h-index
644 publications
44.7K citations
Carnegie Mellon University
Pittsburgh, United States
56 h-index
251 publications
26.8K citations
Tsinghua University
Beijing, China
52 h-index
436 publications
45.2K citations
University of Chinese Academy of Sciences
Beijing, China
47 h-index
276 publications
18.3K citations

Xidian University
Xi'an, China
46 h-index
401 publications
23.1K citations

Shanghai Jiao Tong University
Shanghai, China
44 h-index
381 publications
19.5K citations

Huazhong University of Science and Technology
Wuhan, China
43 h-index
213 publications
12.6K citations

UNSW Sydney
Sydney, Australia
43 h-index
144 publications
15.2K citations
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418 publications · 31.2K citations
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Repository · 396 publications · 19.7K citations
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124 publications · 14.8K citations
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166 publications · 14.5K citations
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128 publications · 12.8K citations
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