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» On the Noise Model of Support Vector Machines Regression
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CDC
2009
IEEE
180views Control Systems» more  CDC 2009»
13 years 12 months ago
Robustness analysis for Least Squares kernel based regression: an optimization approach
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
TNN
2008
142views more  TNN 2008»
13 years 8 months ago
Multiclass Posterior Probability Support Vector Machines
Abstract--Tao et al. have recently proposed the posterior probability support vector machine (PPSVM) which uses soft labels derived from estimated posterior probabilities to be mor...
Mehmet Gönen, Ayse Gönül Tanugur, E...
KDD
2005
ACM
168views Data Mining» more  KDD 2005»
14 years 9 months ago
Nomograms for visualizing support vector machines
We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
ICML
2007
IEEE
14 years 9 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet
CGF
2005
252views more  CGF 2005»
13 years 8 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...