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

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\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, Momentum 0.1
\begin{table}[h]
\begin{tabular}{lrl}
\toprule
Topology & Error & Training time \\ \midrule
160:500:369 & 30.62 \% & \hphantom{0}9min 08s \\
160:500:500:369 & 27.73 \% & 11min 49s \\
160:500:500:500:369 & 34.79 \% & 14min 09s \\
160:500:500:500:500:369 & 33.61 \% & 14min 06s \\
\bottomrule
\end{tabular}
\end{table}
\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}