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ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
16 years 7 days ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
BMCBI
2007
148views more  BMCBI 2007»
15 years 6 months ago
Blast sampling for structural and functional analyses
Background: The post-genomic era is characterised by a torrent of biological information flooding the public databases. As a direct consequence, similarity searches starting with ...
Anne Friedrich, Raymond Ripp, Nicolas Garnier, Emm...
AUSAI
2008
Springer
15 years 8 months ago
Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
ICPR
2006
IEEE
16 years 7 months ago
Human-Robot Interaction by Whole Body Gesture Spotting and Recognition
An intelligent robot is required for natural interaction with humans. Visual interpretation of gestures can be useful in accomplishing natural Human-Robot Interaction (HRI). Previ...
A-Yeon Park, Hee-Deok Yang, Seong-Whan Lee
179
Voted
NIPS
2007
15 years 8 months ago
Second Order Bilinear Discriminant Analysis for single trial EEG analysis
Traditional analysis methods for single-trial classification of electroencephalography (EEG) focus on two types of paradigms: phase locked methods, in which the amplitude of the ...
Christoforos Christoforou, Paul Sajda, Lucas C. Pa...