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» Parallel Support Vector Machines: The Cascade SVM
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BMCBI
2008
88views more  BMCBI 2008»
15 years 4 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...
131
Voted
ICIP
2002
IEEE
16 years 5 months ago
Learning a decision boundary for face detection
This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...
Tae-Kyun Kim, Donggeon Kong, Sang Ryong Kim
SYNASC
2006
IEEE
95views Algorithms» more  SYNASC 2006»
15 years 10 months ago
Evolutionary Support Vector Regression Machines
Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coef...
Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, ...
283
Voted
ISBRA
2011
Springer
14 years 7 months ago
Query-Adaptive Ranking with Support Vector Machines for Protein Homology Prediction
Abstract. Protein homology prediction is a crucial step in templatebased protein structure prediction. The functions that rank the proteins in a database according to their homolog...
Yan Fu, Rong Pan, Qiang Yang, Wen Gao
156
Voted
GECCO
2005
Springer
195views Optimization» more  GECCO 2005»
15 years 9 months ago
Evolutionary strategies for multi-scale radial basis function kernels in support vector machines
In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suit...
Tanasanee Phienthrakul, Boonserm Kijsirikul