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BMCBI
2010
182views more  BMCBI 2010»
14 years 10 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
NAR
2006
89views more  NAR 2006»
14 years 10 months ago
AlgPred: prediction of allergenic proteins and mapping of IgE epitopes
In this study a systematic attempt has been made to integrate various approaches in order to predict allergenic proteins with high accuracy. The dataset used for testing and train...
Sudipto Saha, G. P. S. Raghava
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
14 years 11 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
ESANN
2007
14 years 11 months ago
An Estimation of Response Certainty using Features of Eye-movements
To examine the feasibility of estimating the degree of “strength of belief (SOB)” of viewer’s responses using support vector machines (SVM) trained with features of gazes, t...
Minoru Nakayama, Yosiyuki Takahasi
DCC
2009
IEEE
15 years 10 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang