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\author{ {\fontspec{Trebuchet MS}Marcin Chrz\k{a}szcz} (Universit\"{a}t Z\"{u}rich, IFJ PAN)}
\institute{UZH}
\title[Report from the Heavy Flavor Data Mining Workshop]{Report from the Heavy Flavor Data Mining Workshop}
\date{25 September 2014}
\begin{document}
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{
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\begin{center}
\begin{center}
\begin{columns}
\begin{column}{0.75\textwidth}
\flushright\fontspec{Trebuchet MS}\bfseries \Huge {Report from the Heavy Flavor Data Mining Workshop}
\end{column}
\begin{column}{0.02\textwidth}
{~}
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\quad
\vspace{3em}
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\flushright \vspace{-1.8em} {\fontspec{Trebuchet MS} \Large Marcin Chrząszcz\\\vspace{-0.1em}\small \href{mailto:mchrzasz@cern.ch}{mchrzasz@cern.ch}}
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\vspace{1em}
\footnotesize\textcolor{gray}{Universit\"{a}t Z\"{u}rich, \\ Institute of Nuclear Physics, Polish Academy of Science}\normalsize\\
\vspace{0.5em}
\textcolor{normal text.fg!50!Comment}{Zurich meeting, CERN\\March 4, 2016}
\end{center}
\end{frame}
}
\begin{frame}[c]{Credits where they belong!}
\begin{minipage}{\textwidth}
\begin{center}
\begin{columns}
\column{0.22\textwidth}
\includegraphics[width=0.93\textwidth]{images/pkoppenburg.jpg} \\P. Koppenburg
\column{0.22\textwidth}
\includegraphics[width=0.93\textwidth, height=2cm]{images/tblake.pdf} \\T. Blake
\column{0.22\textwidth}
\includegraphics[width=0.83\textwidth]{images/Marc-OlivierBettler.jpg} \\M. Bettler
\column{0.22\textwidth}
\includegraphics[width=0.93\textwidth]{images/dettori2.jpg} \\F. Dettori
\end{columns}
\begin{columns}
\column{0.22\textwidth}
\column{0.23\textwidth}
\includegraphics[width=0.93\textwidth]{images/andrey.jpg} \\A. Ustyuzhanin
\column{0.27\textwidth}
\includegraphics[width=0.73\textwidth]{images/tatiana.png} \\T. Likhomanenko
\column{0.22\textwidth}
\includegraphics[width=0.85\textwidth]{images/tim.jpg} \\T. Head
\end{columns}
\end{center}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Workshop sponsors}
{~}{~}\\
\begin{minipage}{\textwidth}
\begin{Large}
$\Rrightarrow$ Main sponsors:\\
\begin{center}
\includegraphics[height=1.3cm]{uzh-transp}{~}{~}
\includegraphics[height=1.9cm]{images/intel.jpg}\\
\end{center}
$\Rrightarrow$ Additional support:\\
\begin{center}
\includegraphics[height=1.3cm]{images/cern.jpg}{~}{~}{~}{~}
\includegraphics[height=0.8cm]{images/Yandex.png}
\end{center}
\end{Large}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Some details}
\begin{minipage}{\textwidth}
\begin{itemize}
\item $50+$ participants!
\item A good mixture between the ML and Physics community.
\item Live discussions!
\end{itemize}
\includegraphics[width=0.85\textwidth]{images/group.jpg}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Useful information}
{~}
\begin{minipage}{\textwidth}
\begin{itemize}
\item Indico: \href{https://indico.cern.ch/event/433556/}{\url{https://indico.cern.ch/event/433556/}}
\item Full of interesting talks! Please check them out
\item Let me try to give you a overview:
\end{itemize}
\only<1>{
$\Rrightarrow$ Physics Prize winners:\\
\begin{center}
\includegraphics[rotate=90,width=0.25\textwidth]{images/win.jpg}\\
Alexander Rakhlin, Vicens Gaitan
\end{center}
}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Tutorials}
{~}
\begin{minipage}{\textwidth}
$\Rrightarrow$ We had four ML tutorials in our workshop:
\only<1>{
\begin{columns}
\column{2in}
\begin{itemize}
\item Gilles Louppe (New York Uni), gave a super tutorial on Scikit-Learn.
\item The tutorial was physics oriented $\rightarrow$ examples of training with weights.
\item The material is available on the indico page with Binder.
\item Highly recommend to check it out!
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/giles.png}
\end{columns}
}
\only<2>{
\begin{columns}
\column{2in}
\begin{itemize}
\begin{small}
\item Rafal Jozefowicz (Google Brain), gave a excellent tutorial on the Googles TensorFlow!
\item Since TensorFlow is rather new and most physicists didn't have a chance to hear about it, the tutorial starts from basics!
\item The material is available on the indico page.
\item Please check it out, this looks like something that we as physicist could really benefit from!
\end{small}
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/tensor.png}
\end{columns}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\only<3>{
\begin{columns}
\column{2in}
\begin{itemize}
\item Alison B Lowndes(nVidia), gave a super tutorial on nVidia solutions towards neural networks trainings.
\item Very impressive stuff is done by nVidia.
\item So impressive that some guys from UZH want to try it out in LHCb!
\item Personal view: More effort should be put inside the experiments towards using those cards.
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/nvidia.png}
\end{columns}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\only<4>{
\begin{columns}
\column{2in}
\begin{itemize}
\item Andrey Ustyuzhanin, Aleskei Rogozhnikov (Yandex), gave a great tutorial on using rep.
\item All experiments suffer from reproducibility!
\item A mature solution is proposed.
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/rep.png}
\end{columns}
}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Kaggle Winning solutions}
{~}
\begin{minipage}{\textwidth}
$\Rrightarrow$ We have rewarded Kaggle Physics prize on the workshop:
\only<1>{
\begin{columns}
\column{2in}
\begin{itemize}
\item Vicens Gaitan (Grupo AIA), presented his winning solution.
\item He used so called data-doping technique to reduce data-MC agreement.
\item Vincens did his PhD with LEP experiments so he understands the two worlds.
\item Please check it out as it might be useful for you!
\item \href{https://indico.cern.ch/event/433556/session/0/contribution/13/attachments/1230496/1803471/Zurich_MachineLearning_VicensGaitan.pdf}{\color{blue}Talk}
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/vincen.png}
\end{columns}
}
\only<2>{
\begin{columns}
\column{2in}
\begin{itemize}
\item Alexander Rakhlin, presented his winning solution.
\item He used so called Transfer learning
\item Transfer learning is method that can be used in the trainig if some of the underlying distributions are not well known.
\item I think I don't need to convince anyone that might be usefull in physics ;)
\item \href{https://indico.cern.ch/event/433556/session/0/contribution/14/attachments/1230507/1803492/Flavours_of_Physics.pdf}{\color{blue}Talk}
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/alexander.png}
\end{columns}
}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Open-Space discussion}
{~}{~}
\begin{minipage}{\textwidth}
\only<1>{
\begin{columns}
\column{2in}
\begin{itemize}
\item As an experiment we had a Open-Space discussion.
\item It turns out that one can have meetings without conveners ;)
\item \href{https://indico.cern.ch/event/433556/session/2/contribution/18/attachments/1231744/1806021/open-space-overview.pdf}{\color{blue}Summary Talk}
\end{itemize}
\column{3in}
\includegraphics[width=0.95\textwidth]{images/open.png}
\end{columns}
}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Other interesting talks}
{~}{~}
\begin{minipage}{\textwidth}
\begin{center}
\begin{itemize}
\item Automatic Tuning of Hyperparameters
\item Classifier output calibration to probability
\item Classifiers for centrality determination in proton-nucleus and nucleus-nucleus collisions
\item Data Fusion Surogate Modeling on Incomplete Factorial Design of Experiments
\item Mathematics of Big Data
\item OpenML: Collaborative machine learning
\item Boosting applications for HEP
\item Efficient Elastic Net Regularization for Sparse Linear Models in the Multilabel Setting
\item Deep Learning for event reconstruction
\end{itemize}
\end{center}
\end{minipage}
\vspace*{2.cm}
\end{frame}
\begin{frame}[c]{Summary}
{~}{~}
\begin{minipage}{\textwidth}
$\Rrightarrow$ I hope I interest you enough that you check out the workshop!\\
$\Rrightarrow$ The workshop was a success and future events like this should happen!
\end{minipage}
\vspace*{2.cm}
\end{frame}
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mchrzasz