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» Co-Tracking Using Semi-Supervised Support Vector Machines
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CIDM
2009
IEEE
16 years 1 months ago
An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented software
—  Identifying faulty classes in object-oriented software is one of the important software quality assurance activities. This paper empirically investigates the application of t...
Hamoud I. Aljamaan, Mahmoud O. Elish
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
16 years 27 days ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
ICC
2007
IEEE
141views Communications» more  ICC 2007»
16 years 20 days ago
Accurate Classification of the Internet Traffic Based on the SVM Method
—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
Zhu Li, Ruixi Yuan, Xiaohong Guan
NSDI
2008
15 years 8 months ago
Ghost Turns Zombie: Exploring the Life Cycle of Web-based Malware
While the web provides information and services that enrich our lives in many ways, it has also become the primary vehicle for delivering malware. Once infected with web-based mal...
Michalis Polychronakis, Niels Provos
ESANN
2008
15 years 7 months ago
Discrimination of regulatory DNA by SVM on the basis of over- and under-represented motifs
In this paper we apply three pattern recognition methods (support vector machine, cluster analysis and principal component analysis) to distinguish regulatory regions from coding a...
Rene te Boekhorst, Irina I. Abnizova, Lorenz Werni...