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» Training Data Selection for Support Vector Machines
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BMCBI
2010
227views more  BMCBI 2010»
13 years 8 months ago
Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage
Background: HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-recepto...
Majid Masso, Iosif I. Vaisman
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
14 years 2 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
RECOMB
2004
Springer
14 years 8 months ago
A class of edit kernels for SVMs to predict translation initiation sites in eukaryotic mRNAs
The prediction of translation initiation sites (TISs) in eukaryotic mRNAs has been a challenging problem in computational molecular biology. In this paper, we present a new algori...
Haifeng Li, Tao Jiang
SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
14 years 5 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
JMLR
2006
186views more  JMLR 2006»
13 years 7 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani