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» Geometric Neural Networks and Support Multi-Vector Machines
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ANNPR
2006
Springer
13 years 11 months ago
Incremental Training of Support Vector Machines Using Truncated Hypercones
We discuss incremental training of support vector machines in which we approximate the regions, where support vector candidates exist, by truncated hypercones. We generate the trun...
Shinya Katagiri, Shigeo Abe
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 7 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
IWANN
2001
Springer
13 years 12 months ago
Non-symmetric Support Vector Machines
A novel approach to calculate the generalization error of the support vector machines and a new support vector machine–nonsymmatic support vector machine–is proposed here. Our ...
Jianfeng Feng
ICCS
2007
Springer
14 years 1 months ago
Text Classification with Support Vector Machine and Back Propagation Neural Network
Abstract. We compared a support vector machine (SVM) with a back propagation neural network (BPNN) for the task of text classification of XiangShan science conference (XSSC) web do...
Wen Zhang, Xijin Tang, Taketoshi Yoshida
ANNPR
2006
Springer
13 years 11 months ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe