A short Introduction to Support Vector Machines and Kernelbased Learning

Suykens J.

• Disadvantages of classical neural nets• SVM properties and standard SVM classifier• Related kernelbased learning methods• Use of the “kernel trick” (Mercer Theorem)• LS-SVMs: extending the SVM framework• Towards a next generation of universally applicable models?• The problem of learning and generalization