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CORR
2008
Springer
159views Education» more  CORR 2008»
15 years 4 months ago
Face Detection Using Adaboosted SVM-Based Component Classifier
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,...
IJCSA
2008
132views more  IJCSA 2008»
15 years 4 months ago
Biomedical Named Entity Recognition Based on Classifiers Ensemble
In this paper, we present classifiers ensemble approaches for biomedical named entity recognition. Generalized Winnow, Conditional Random Fields, Support Vector Machine, and Maxim...
Haochang Wang, Tiejun Zhao, Hongye Tan, Shu Zhang
JAIR
2006
113views more  JAIR 2006»
15 years 4 months ago
Generative Prior Knowledge for Discriminative Classification
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
Arkady Epshteyn, Gerald DeJong
JCP
2006
102views more  JCP 2006»
15 years 4 months ago
Efficient Formulations for 1-SVM and their Application to Recommendation Tasks
The present paper proposes new approaches for recommendation tasks based on one-class support vector machines (1-SVMs) with graph kernels generated from a Laplacian matrix. We intr...
Yasutoshi Yajima, Tien-Fang Kuo
NECO
2008
112views more  NECO 2008»
15 years 4 months ago
Second-Order SMO Improves SVM Online and Active Learning
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Tobias Glasmachers, Christian Igel