Robustness and Regularization of Support Vector Machines

author: Huan Xu, Department of Mechanical Engineering, National University of Singapore
published: Dec. 20, 2008,   recorded: December 2008,   views: 405
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Description

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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