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» Support Vector Machines: Theory and Applications
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ICASSP
2010
IEEE
13 years 8 months ago
Multi-class SVM optimization using MCE training with application to topic identification
This paper presents a minimum classification error (MCE) training approach for improving the accuracy of multi-class support vector machine (SVM) classifiers. We have applied th...
Timothy J. Hazen
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
ICPR
2004
IEEE
14 years 9 months ago
Learning Sample Subspace with Application to Face Detection
In this paper, we present a novel maximum correlation sample subspace method and apply it to human face detection [1] in still images. The algorithm starts by projecting all the t...
Guoping Qiu, Jianzhong Fang
KDD
2007
ACM
202views Data Mining» more  KDD 2007»
14 years 9 months ago
Support feature machine for classification of abnormal brain activity
In this study, a novel multidimensional time series classification technique, namely support feature machine (SFM), is proposed. SFM is inspired by the optimization model of suppo...
Wanpracha Art Chaovalitwongse, Ya-Ju Fan, Rajesh C...
BMCBI
2007
153views more  BMCBI 2007»
13 years 8 months ago
Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
Matthew Landry, Stephen Winters-Hilt