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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
KDD
2005
ACM
205views Data Mining» more  KDD 2005»
15 years 2 months ago
Feature bagging for outlier detection
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Aleksandar Lazarevic, Vipin Kumar
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
12 years 12 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
DPD
2002
125views more  DPD 2002»
14 years 9 months ago
Parallel Mining of Outliers in Large Database
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...
Edward Hung, David Wai-Lok Cheung
ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
15 years 3 months ago
Parallel Algorithms for Distance-Based and Density-Based Outliers
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Elio Lozano, Edgar Acuña