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ICCV
2007
IEEE
14 years 1 months ago
Support Kernel Machines for Object Recognition
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
Ankita Kumar, Cristian Sminchisescu
SWARM
2010
SPRINGER
154views Optimization» more  SWARM 2010»
13 years 5 months ago
An Immune Concentration Based Virus Detection Approach Using Particle Swarm Optimization
This paper proposes an immune concentration based virus detection approach which utilizes a two-element concentration vector to construct the feature. In this approach, ‘self’ ...
Wei Wang, Pengtao Zhang, Ying Tan
ISCI
2008
165views more  ISCI 2008»
13 years 6 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
BMCBI
2007
142views more  BMCBI 2007»
13 years 6 months ago
Predicting and improving the protein sequence alignment quality by support vector regression
Background: For successful protein structure prediction by comparative modeling, in addition to identifying a good template protein with known structure, obtaining an accurate seq...
Minho Lee, Chan-seok Jeong, Dongsup Kim
PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
14 years 1 months ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario