LaTeX-examples/presentations/Bachelor-Short/LaTeX/neural-nets.tex

\subsection{Neural Net experiments}
\begin{frame}{Experiments}
    \textbf{Preprocessing:} Scaling, shifting and linear interpolation\\
    \textbf{Features:} Coordinates of 80 points (4 strokes with 20 points each)\\
    \textbf{Learning:} MLP, 300 epochs, LR of 0.1
    \begin{itemize}
        \item[] \textit{toplogy       \tabto{6cm} error in training time}
        \item 160:500:369             \tabto{6cm} 30.62 \% in \hphantom{0}9min 08s
        \item 160:500:500:369         \tabto{6cm} 27.73 \% in 11min 49s
        \item 160:500:500:500:369     \tabto{6cm} 34.79 \% in 14min 09s
        \item 160:500:500:500:500:369 \tabto{6cm} 33.61 \% in 14min 06s
    \end{itemize}
\end{frame}

\begin{frame}[fragile]{Examples of confusable symbols}
\begin{table}[ht]
    \centering
    \begin{tabular}{lc|lc}
        \textbf{\LaTeX}& \textbf{Rendered}   & \textbf{\LaTeX}& \textbf{Rendered} \\\midrule
        \verb+\sum+    & $\sum$         & \verb+$\Sigma$+        & $\Sigma$\\
        \verb+\coprod+ & $\coprod$      & \verb+$\amalg$+        & $\amalg$\\
        \verb+\perp+   & $\perp$        & \verb+$\bot$+          & $\bot$\\
        \verb+\models+ & $\models$      & \verb+$\vDash$+        & $\vDash$\\
        \verb+\emptyset+ & $\emptyset$  & \verb+$\diameter$+     & $\diameter$\\
        ~              & ~              & \verb+$\o$+            & $\o$\\
        ~              & ~              & \verb+$\varnothing$+   & $\varnothing$\\
        \verb+\Delta+  & $\Delta$       & \verb+$\triangle$+     & $\triangle$\\
        \verb+\varepsilon+ & $\varepsilon$ & \verb+$\mathcal{E}$+ & $\mathcal{E}$\\
    \end{tabular}
\end{table}

When those confusions are not counted as errors, the current best system
has an classification error rate of $12.7 \%$ (otherwise $22.2 \%$).

\end{frame}