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KDD
2002
ACM
113views Data Mining» more  KDD 2002»
15 years 10 months ago
Scalable robust covariance and correlation estimates for data mining
Covariance and correlation estimates have important applications in data mining. In the presence of outliers, classical estimates of covariance and correlation matrices are not re...
Fatemah A. Alqallaf, Kjell P. Konis, R. Douglas Ma...
KDD
2007
ACM
220views Data Mining» more  KDD 2007»
15 years 10 months ago
SCAN: a structural clustering algorithm for networks
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
BMCBI
2008
218views more  BMCBI 2008»
14 years 9 months ago
LOSITAN: A workbench to detect molecular adaptation based on a Fst-outlier method
Background: Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to u...
Tiago Antao, Ana Lopes, Ricardo J. Lopes, Albano B...
CVPR
2010
IEEE
14 years 9 months ago
Illumination compensation based change detection using order consistency
We present a change detection method resistant to global and local illumination variations for use in visual surveillance scenarios. Approaches designed thus far for robustness to...
Vasu Parameswaran, Maneesh Singh, Visvanathan Rame...
ICPR
2008
IEEE
15 years 4 months ago
On-line novelty detection using the Kalman filter and extreme value theory
Novelty detection is concerned with identifying abnormal system behaviours and abrupt changes from one regime to another. This paper proposes an on-line (causal) novelty detection...
Hyoungjoo Lee, Stephen J. Roberts