prosem2/slides.tex

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\section{Organisation}
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\frametitle{Today}
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\begin{itemize}
\item Kick-Off Meeting
\item Some Formalities
\item Short Overview of the Topics
\end{itemize}
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\begin{itemize}
\item Organised by
\item Chiara Balestra (chiara.balestra@cs.uni-dortmund.de)
\item Simon Klüttermann (simon.kluettermann@cs.tu-dortmund.de)
\end{itemize}
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\frametitle{Objective of this Seminar}
\begin{itemize}
\item Introduction to some fundamental research problems
\begin{itemize}
\item Researching current scientific ideas
\item Understanding benefits and drawbacks of state-of-the-art techniques
\item Writing a clear and concisive scientific report
\item Presenting and discussing your findings
\end{itemize}
\end{itemize}
\rightarrow Great start for a bachelor thesis.... \rightarrow maybe just talk to your supervisor about this
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\frametitle{Timeline}
\begin{enumerate}
\item Kick-Off Meeting
\item Choose Topics till 10.10.2022
\item Talk to your supervisor once till 08.11.2022 %let us change this date to something like 28.Oct
\item 5min Presentations of your Topic on 08.11.2022 % this is a bank holiday. 02.11 fits better
\item Write your abstract till 15.11.2022
\item Presentation in Class (end of January/beginning February)
\item Discussion of your Findings (afterwards)
\item Writing of your Report (till two weeks later)
\end{enumerate}
\begin{itemize}
\item All parts required!
\end{itemize}
\vspace{2em}
\begin{itemize}
\item Everything will be done in english. If this is a problem for you, please write us.
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\frametitle{Tasks of this Seminar}
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% \item Required: willingless to learn something new
% \item Also useful: A basic understanding of machine learning, statistics and linear algebra
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\begin{enumerate}
\item Choose a couple of topics from our list, you will be assigned to one of them
\item Read and understand the chapter/paper given to you
\item Find, read and understand related literature. It is probably impossible to get a good picture about your topic from just one paper (and chapter)
\item Critically analyze the suggested ideas and compare them to the literature
\end{enumerate}
\begin{itemize}
\item Presentation course (included):
\begin{itemize}
\item 5min presentation of your topic
\item Write an abstract and get feedback
\end{itemize}
\item Final Results:
\begin{itemize}
\item Presentation (25-30min +10min discussion)
\item Written Report (at least 6 Pages double column, ACM template)
\end{itemize}
\end{itemize}
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\frametitle{Research Culture}
This course is Research oriented
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\begin{itemize}
\item Feel free to ask as many Questions as you want
\item If you want to discuss your Topic with somebody, make an appointment with your Supervisor
\item suggestion: Every two weeks!
\item But at least once:
\begin{itemize}
\item before your 5min Presentation,
\item before your Presentation,
\item before your Report to discuss the Presentation
\end{itemize}
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\section{Topics}
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\frametitle{Topics}
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\begin{itemize}
\item Based on the Book "Interpretable Machine Learning" by Christoph Molnar
\item Freely available at christophm.github.io/interpretable-ml-book
\end{itemize}
\begin{itemize}
\item Some Topics contain programming assignments. We suggest using google colab for these.
\end{itemize}
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\begin{center}
\begin{table}[]
\begin{tabular}{|l|l|l|l|}
\hline
1: Why IML & 2: How IML & 3: Linear ML & 4: Trees \\ \hline
5: Rules & 6: PDP & 7: ALE & 8: Interactions \\ \hline
9: Decomposition & 10: Permutations & 11: Surrogates & 12: Prototypes \\ \hline
13: ICE & 14: Counterfactuals & 15: Shapley Values & 16: Learned Features \\ \hline
17: Saliency Maps & 18: Concepts & 19: Adversarials & 20: Influential Instances \\ \hline
\end{tabular}
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% \item 1: Prototypes
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% \item 3: Pixel Attribution
% \item 4: Shapley Values
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