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» Choosing Multiple Parameters for Support Vector Machines
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NECO
2008
108views more  NECO 2008»
13 years 7 months ago
An SMO Algorithm for the Potential Support Vector Machine
We describe a fast Sequential Minimal Optimization (SMO) procedure for solving the dual optimization problem of the recently proposed Potential Support Vector Machine (P-SVM). The...
Tilman Knebel, Sepp Hochreiter, Klaus Obermayer
JISE
2010
144views more  JISE 2010»
13 years 2 months ago
Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
Li-Jen Chien, Chien-Chung Chang, Yuh-Jye Lee
DSD
2004
IEEE
106views Hardware» more  DSD 2004»
13 years 11 months ago
Finite Precision Analysis of Support Vector Machine Classification in Logarithmic Number Systems
In this paper we present an analysis of the minimal hardware precision required to implement Support Vector Machine (SVM) classification within a Logarithmic Number System archite...
Faisal M. Khan, Mark G. Arnold, William M. Potteng...
CGF
2005
252views more  CGF 2005»
13 years 7 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
ICASSP
2010
IEEE
13 years 8 months ago
Training a support vector machine to classify signals in a real environment given clean training data
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...