Robustness and Regularization of Support Vector Machines
published: Dec. 20, 2008, recorded: December 2008, views: 406
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We consider a robust classiﬁcation problem and show that standard regularized SVM is a special case of our formulation, providing an explicit link between reg- ularization and robustness. At the same time, the physical connection of noise and robustness suggests the potential for a broad new family of robust classiﬁcation algorithms. Finally, we show that robustness is a fundamental property of classi- ﬁcation algorithms, by re-proving consistency of support vector machines using only robustness arguments (instead of VC dimension or stability).
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