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TNN
2008
97views more  TNN 2008»
13 years 7 months ago
Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
Liefeng Bo, Ling Wang, Licheng Jiao
TNN
2008
152views more  TNN 2008»
13 years 7 months ago
Distributed Parallel Support Vector Machines in Strongly Connected Networks
We propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange...
Yumao Lu, Vwani P. Roychowdhury, L. Vandenberghe
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...
ICML
2005
IEEE
14 years 8 months ago
A support vector method for multivariate performance measures
This paper presents a Support Vector Method for optimizing multivariate nonlinear performance measures like the F1score. Taking a multivariate prediction approach, we give an algo...
Thorsten Joachims
ICML
2003
IEEE
14 years 8 months ago
Low Bias Bagged Support Vector Machines
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction technique. This suggests that bagging should be applied to learning algorithms ...
Giorgio Valentini, Thomas G. Dietterich