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» Feature selection for linear support vector machines
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ICIP
2001
IEEE
14 years 9 months ago
Higher order autocorrelations for pattern classification
The use of higher-order local autocorrelations as features for pattern recognition has been acknowledged since many years, but their applicability was restricted to relatively low...
Vlad Popovici, Jean-Philippe Thiran
CVPR
2005
IEEE
14 years 10 months ago
A Weighted Nearest Mean Classifier for Sparse Subspaces
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
Cor J. Veenman, David M. J. Tax
ICML
2005
IEEE
14 years 8 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
PROMISE
2010
13 years 2 months ago
How effective is Tabu search to configure support vector regression for effort estimation?
Background. Recent studies have shown that Support Vector Regression (SVR) has an interesting potential in the field of effort estimation. However applying SVR requires to careful...
Anna Corazza, Sergio Di Martino, Filomena Ferrucci...
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 5 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic