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Supervised Learning by Support Vector Machines

  • Gabriele Steidl

Abstract

During the last 2 decades support vector machine learning has become a very active field of research with a large amount of both sophisticated theoretical results and exciting real-word applications. This chapter gives a brief introduction into the basic concepts of supervised support vector learning and touches some recent developments in this broad field.

Keywords

Support Vector Machine Loss Function Support Vector Regression Dual Problem Sparse Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • Gabriele Steidl

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