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ALT
2000
Springer
10 years 11 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...
NECO
2011
9 years 9 months ago
Least Squares Estimation Without Priors or Supervision
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Martin Raphan, Eero P. Simoncelli
BMCBI
2005
131views more  BMCBI 2005»
10 years 2 months ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...
ASC
2008
10 years 2 months ago
Dynamic classification for video stream using support vector machine
A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new `incremental' framework for multiple-classifying video stream da...
Mariette Awad, Yuichi Motai
DICTA
2003
10 years 4 months ago
Algebraic Curve Fitting Support Vector Machines
An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the problem of fitting an algebraic curve to a set of vectors given an additional set of v...
Christian J. Walder, Brian C. Lovell, Peter J. Koo...
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