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* iterate t1t2 * restructure and iterate * cleanup * wrap up * iterate
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w15_wrap_up/t01_intro.pdf → w14_pratical_considerations/t01_intro.pdf
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\input{t00_template.tex} | ||
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\usepackage[normalem]{ulem} | ||
\usepackage{pifont} | ||
\usepackage{relsize} | ||
\renewcommand{\lit}[1]{{\smaller\color{black!60}[#1]}} | ||
\title[AutoML: Practical]{AutoML: Practical Considerations} | ||
\subtitle{Introduction} | ||
\author[Janek Thomas]{Bernd Bischl \and Frank Hutter \and Lars Kotthoff\newline \and Marius Lindauer \and \underline{Janek Thomas} \and Joaquin Vanschoren} | ||
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\begin{document} | ||
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\maketitle | ||
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%---------------------------------------------------------------------- | ||
%---------------------------------------------------------------------- | ||
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\begin{frame}{From HPO to AutoML} | ||
So far we covered | ||
\begin{itemize} | ||
\item HPO as black-box optimization | ||
\begin{itemize} | ||
\item Grid- and random search, EAs, BO | ||
\end{itemize} | ||
\item Speedup techniques for HPO | ||
\begin{itemize} | ||
\item Multi-fidelity, meta-learning, ... | ||
\end{itemize} | ||
\item Multi-objective HPO | ||
\begin{itemize} | ||
\item NSGA-II, ParEGO, ... | ||
\end{itemize} | ||
\item Neural Architecture Search (NAS) | ||
\begin{itemize} | ||
\item One-Shot approaches, DARTS, ... | ||
\end{itemize} | ||
\end{itemize} | ||
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\vspace{1cm} | ||
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$\longrightarrow$ So far we haven't talked (much) about practical considerations. | ||
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\end{frame} | ||
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\begin{frame}{From HPO to AutoML} | ||
\begin{center} | ||
\includegraphics[width = 0.9\linewidth]{images/18_AutoML-Components-Overview-Infographic_corrected.png} | ||
\end{center} | ||
\end{frame} | ||
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\begin{frame}{What is missing?} | ||
\begin{columns} | ||
\begin{column}{0.5\textwidth} | ||
What do I need to know as an AutoML user? | ||
\begin{itemize} | ||
\item \sout{Nothing, because it is automatic.} | ||
\item Understand limitations of AutoML and framework. | ||
\item Know how to interpret the results. | ||
\item Maybe: Data cleaning and feature extraction. | ||
\end{itemize} | ||
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\vspace{1em} | ||
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Ingredients to implement an AutoML system? | ||
\begin{itemize} | ||
\item HPO algorithm | ||
\item ML / Pipeline framework | ||
\item Parallelization / Multi-fidelity | ||
\item Process encapsulation and time capping | ||
\item ... | ||
% \item (Preprocessing) | ||
\end{itemize} | ||
\end{column}% | ||
\begin{column}{0.5\textwidth} | ||
\begin{center} | ||
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Practitioners view: | ||
\scalebox{0.45}{ | ||
\input{tikz/true_automl_overview.tex} | ||
} | ||
\vspace{1em} | ||
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Academic view: | ||
\scalebox{0.45}{ | ||
\input{tikz/automl_overview.tex} | ||
} | ||
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\end{center} | ||
\end{column} | ||
\end{columns} | ||
\end{frame} | ||
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\end{document} |
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