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CONEXT
2007
ACM
13 years 10 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
JAIR
2006
113views more  JAIR 2006»
13 years 8 months ago
Generative Prior Knowledge for Discriminative Classification
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
Arkady Epshteyn, Gerald DeJong
TKDE
2008
123views more  TKDE 2008»
13 years 8 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
ICML
2003
IEEE
14 years 9 months ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
BMCBI
2004
123views more  BMCBI 2004»
13 years 8 months ago
Interaction profile-based protein classification of death domain
Background: The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experim...
Drew Lett, Michael Hsing, Frederic Pio