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» Prediction of Contact Maps Using Support Vector Machines
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ICCV
2009
IEEE
13 years 6 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
BMCBI
2008
140views more  BMCBI 2008»
13 years 8 months ago
SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
Background: Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologou...
Lukasz A. Kurgan, Krzysztof J. Cios, Ke Chen 0003
TNN
2008
129views more  TNN 2008»
13 years 8 months ago
Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
Johan A. K. Suykens
ESANN
2008
13 years 10 months ago
Survival SVM: a practical scalable algorithm
This work advances the Support Vector Machine (SVM) based approach for predictive modelling of failure time data as proposed in [1]. The main results concern a drastic reduction in...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
WSCG
2004
188views more  WSCG 2004»
13 years 9 months ago
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used as neural input signals ...
Chih-I. Hung, Po-Lei Lee, Yu-Te Wu, Hui-Yun Chen, ...