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ICML
2008
IEEE
14 years 6 months ago
Fast support vector machine training and classification on graphics processors
Bryan C. Catanzaro, Narayanan Sundaram, Kurt Keutz...
ICANN
2001
Springer
13 years 10 months ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
ANNPR
2006
Springer
13 years 9 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
TIP
2008
128views more  TIP 2008»
13 years 5 months ago
Wavelet Frame Accelerated Reduced Support Vector Machines
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
SDM
2010
SIAM
151views Data Mining» more  SDM 2010»
13 years 7 months ago
Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
The high computational cost of nonlinear support vector machines has limited their usability for large-scale problems. We propose two novel stochastic algorithms to tackle this pr...
Hua Ouyang, Alexander Gray