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ISCI
2008
165views more  ISCI 2008»
13 years 8 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
ALT
2000
Springer
14 years 5 months ago
On the Noise Model of Support Vector Machines Regression
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
Massimiliano Pontil, Sayan Mukherjee, Federico Gir...
CIRA
2007
IEEE
147views Robotics» more  CIRA 2007»
14 years 2 months ago
Local Online Support Vector Regression for Learning Control
—Support vector regression (SVR) is a class of machine learning technique that has been successfully applied to low-level learning control in robotics. Because of the large amoun...
Younggeun Choi, Shin-Young Cheong, Nicolas Schweig...
IMSCCS
2006
IEEE
14 years 2 months ago
Estimation Of Cross-Hybridization Signals Using Support Vector Regression
Microarray technology is a powerful biotechnology tool which allows researchers to simultaneously evaluate the expression of thousands of genes, if not the entire expressed genome...
Yijun Sun, Li Liu, Mick Popp, William G. Farmerie
NIPS
2003
13 years 10 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...