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» Modeling Discriminative Global Inference
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BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
FASE
2004
Springer
14 years 26 days ago
Checking Absence of Illicit Applet Interactions: A Case Study
Abstract. This paper presents the use of a method – and its corresponding tool set – for compositional verification of applet interactions on a realistic industrial smart card...
Marieke Huisman, Dilian Gurov, Christoph Sprenger,...
NIPS
2008
13 years 9 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
BMCBI
2007
194views more  BMCBI 2007»
13 years 7 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
CVPR
2007
IEEE
14 years 9 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann