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IJCNN
2008
IEEE
13 years 11 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe
ICIC
2005
Springer
13 years 10 months ago
Signature Verification Using Wavelet Transform and Support Vector Machine
In this paper, we propose a novel on-line handwritten signature verification method. Firstly, the pen-position parameters of the on-line signature are decomposed into multiscale si...
Hong-Wei Ji, Zhong-Hua Quan
DICTA
2003
13 years 6 months ago
Algebraic Curve Fitting Support Vector Machines
An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the problem of fitting an algebraic curve to a set of vectors given an additional set of v...
Christian J. Walder, Brian C. Lovell, Peter J. Koo...
OL
2007
103views more  OL 2007»
13 years 4 months ago
Support vector machine via nonlinear rescaling method
In this paper we construct the linear support vector machine (SVM) based on the nonlinear rescaling (NR) methodology (see [9, 11, 10] and references therein). The formulation of t...
Roman A. Polyak, Shen-Shyang Ho, Igor Griva
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 5 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys