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KDD
2005
ACM
205views Data Mining» more  KDD 2005»
13 years 10 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
TSP
2008
117views more  TSP 2008»
13 years 5 months ago
Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a mathematically justifiable, com...
R. R. Nadakuditi, A. Edelman
CSDA
2008
158views more  CSDA 2008»
13 years 5 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner
ICIP
2004
IEEE
14 years 7 months ago
Defect detection on hardwood logs using high resolution three dimensional laser scan data
The location, type, and severity of external defects on hardwood logs and stems are the primary indicators of overall log quality and value. External defects provide hints about t...
Liya Thomas, Lamine Mili, Clifford A. Shaffer, Ed ...
CSDA
2007
152views more  CSDA 2007»
13 years 5 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch