565 search results - page 1 / 113 » A Generalized Quadratic Loss for Support Vector Machines |
ECAI
2004
Springer
13 years 10 months ago
2004
Springer
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
INFORMATICALT
2011
12 years 11 months ago
2011
To set the values of the hyperparameters of a support vector machine (SVM), the method of choice is cross-validation. Several upper bounds on the leave-one-out error of the pattern...
ALT
2000
Springer
14 years 1 months ago
2000
Springer
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),...
NIPS
2008
13 years 6 months ago
2008
We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow�...
ALT
2004
Springer
14 years 1 months ago
2004
Springer
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...