\beamer@endinputifotherversion {3.36pt}
\beamer@sectionintoc {1}{Linear SVM's}{4}{0}{1}
\beamer@subsectionintoc {1}{1}{The margin and the expected classification error}{4}{0}{1}
\beamer@subsectionintoc {1}{2}{Maximum Margin Linear classifiers}{5}{0}{1}
\beamer@subsectionintoc {1}{3}{Linear classifiers for non-linearly separable data}{12}{0}{1}
\beamer@sectionintoc {2}{Non linear SVM}{15}{0}{2}
\beamer@subsectionintoc {2}{1}{The ``kernel trick''}{15}{0}{2}
\beamer@subsectionintoc {2}{2}{Kernels}{19}{0}{2}
\beamer@subsectionintoc {2}{3}{Prediction with SVM}{23}{0}{2}
\beamer@sectionintoc {3}{Extensions}{24}{0}{3}
\beamer@subsectionintoc {3}{1}{$L_1$ SVM}{24}{0}{3}
\beamer@subsectionintoc {3}{2}{Multi-class and One class SVM}{25}{0}{3}
\beamer@subsectionintoc {3}{3}{SV Regression}{26}{0}{3}
\beamer@subsectionintoc {4}{1}{A simple optimization example}{33}{1}{3}
\beamer@subsectionintoc {5}{1}{A simple SVM problem}{37}{1}{3}