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» Outlier Detection for High Dimensional Data
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NN
2010
Springer
183views Neural Networks» more  NN 2010»
14 years 7 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui
89
Voted
IPPS
2008
IEEE
15 years 3 months ago
Outlier detection in performance data of parallel applications
— When an adaptive software component is employed to select the best-performing implementation for a communication operation at runtime, the correctness of the decision taken str...
Katharina Benkert, Edgar Gabriel, Michael M. Resch
DAGSTUHL
2007
14 years 11 months ago
Subspace outlier mining in large multimedia databases
Abstract. Increasingly large multimedia databases in life sciences, ecommerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in d...
Ira Assent, Ralph Krieger, Emmanuel Müller, T...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 9 months ago
Detecting outliers using transduction and statistical testing
Outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. Although there has been a significant amount of work in outlier detection, ...
Daniel Barbará, Carlotta Domeniconi, James ...
CORR
2010
Springer
64views Education» more  CORR 2010»
14 years 9 months ago
High-Dimensional Matched Subspace Detection When Data are Missing
We consider the problem of deciding whether a highly incomplete signal lies within a given subspace. This problem, Matched Subspace Detection, is a classical, wellstudied problem w...
Laura Balzano, Benjamin Recht, Robert Nowak