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add several slides and delete template ones

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lukas-heiligenbrunner 2023-03-20 11:39:36 +01:00
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commit 88a55247d0
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presentation/main.tex
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@ -3,7 +3,7 @@
% Struktur und Pointer Referat
% 20.04.2020
%----------------------------------------------------------------------------------------
\usetheme[nofirafonts]{focus}
\usetheme{focus}
\usepackage[utf8]{inputenc}
@ -68,27 +68,28 @@
\begin{frame}
\maketitle
\end{frame}
%----------------------------------------------------------------------------------------
% SECTION 1
%----------------------------------------------------------------------------------------
% todo pic of action
\section{The goal}
\begin{frame}{The goal}
\begin{itemize}
\item train model
\item recognize action of person
\item from video [$\approx$10sec]
\item eg.:
\begin{itemize}
\item brushing hair
\item riding bike
\item dancing
\item playing violin
\item train model
\item recognize action of person
\item from video [$\approx$10sec]
\item eg.:
\begin{itemize}
\item brushing hair
\item riding bike
\item dancing
\item playing violin
\end{itemize}
\item as generic as possible
\end{itemize}
\end{itemize}
\end{frame}
%----------------------------------------------------------------------------------------
@ -104,16 +105,16 @@
\begin{itemize}
\item Supervised action recoginition
\begin{itemize}
\item lots of labeled samples necessary
\item videos
\item lots of labeled samples necessary
\item videos
\end{itemize}
\item Labeling Samples very expensive
\begin{itemize}
\item avoid!
\item Avoid!
\end{itemize}
\item Tremendous amount of unlabled data
\begin{itemize}
\item YouTube
\item YouTube
\end{itemize}
\item using semi-supervised learning might be benefitial
\end{itemize}
@ -121,18 +122,50 @@
%------------------------------------------------
\begin{frame}{Whats already been done}
\begin{itemize}
\item pseudo-labeling
\end{itemize}
\begin{frame}{What's all about Semi supervised?}
\begin{itemize}
\item Supervised learning
\begin{itemize}
\item Data samples
\item Target labels
\item Each sample is associated to target label
\end{itemize}
\item Unsupervised learning
\begin{itemize}
\item Data samples
\item target is to find patterns in data
\item without supervision
\end{itemize}
\item Semi-Supervised learning
\begin{itemize}
\item combination of both
\item have labeled \& unlabeled data
\item labeled data guides learning process
\item unlabled helps to gain additional information
\item goal is performance improvement
\end{itemize}
\end{itemize}
\end{frame}
%------------------------------------------------
\begin{frame}{Pointer in Java}
\begin{frame}[allowframebreaks]{What's already been done}
\begin{itemize}
\item Alle Objekte automatisch Pointer
\item Primitives (int, float, double) keine Pointer
\item Pseudo-labeling
\item Train model on labeled data
\begin{itemize}
\item Eg. 1\% of data labeled
\end{itemize}
\item Confidence of prediction
\item If high enough
\item Use to predict unlabeled data
\end{itemize}
\framebreak
\begin{itemize}
\item quantity and quality of pseudo-labels
\item significant impact on main model accuracy!
\item we want to improve pseudo-label framework as much as possible
\end{itemize}
\end{frame}
@ -140,179 +173,50 @@
% SECTION 2
%----------------------------------------------------------------------------------------
\section{Cross-Model Pseudo-Labeling}
\section{Strukturen} % Section title slide, unnumbered
%------------------------------------------------
\begin{frame}{Strukturen Allgemein}
\begin{frame}[allowframebreaks]{Papers approach}
\begin{itemize}
\item kategorisieren von Variablen
\item Based on complementary-representations of model
\item Models of different size
\item Different structural-bias $\rightarrow$ different category-wise performance
\item Small model
\begin{itemize}
\item Variablen \textit{(int, char, double, float)}
\item Pointer
\item Arrays
\item lower capacity
\item better captures temporal dynamics in recognizing actions
\end{itemize}
\item Large model
\begin{itemize}
\item better learns spatial semantics
\item to distinguish different action instances
\end{itemize}
\item Keyword \textit{struct}
\item verbessert Übersicht
\item Schritt Richtung Objektorientierung
\item ideal für Listen und Baumstruktur
\end{itemize}
\end{frame}
%------------------------------------------------
\begin{frame}[fragile, allowframebreaks]{C Syntax}
Definition:
\begin{lstlisting}
struct Adresse {
char name[50];
int *nummer;
short hausnummer;
long plz;
};\end{lstlisting}
Anwendung:
\begin{lstlisting}
// Variable der Struktur erstellen
struct Adresse adresseKurt;
// Zugriff auf die Elemente
strcpy(adresseKurt.name, "Kurt Kanns");
adresseKurt.hausnummer = 23;
int nr = 4;
adresseKurt.nummer = &nr;
adresseKurt.plz = 45678;\end{lstlisting}
\framebreak
Typdefinition mit typedef:
\begin{lstlisting}
struct Adresse {
char name[50];
short hausnummer;
};
typedef struct Adresse Adr;
Adr a1,a2; // Datentyp Adr
\end{lstlisting}
Kombination:
\begin{lstlisting}
typedef struct Adresse {
char name[50];
short hausnummer;
} Adr;
Adr a1,a2; // Datentyp Adr
\end{lstlisting}
\end{frame}
\begin{frame}{Sonstiges}
\begin{itemize}
\item Strukturtypdeklaration: struct Adresse \{…\};
\item Zugriff auf einzelne Komponenten durch\\
Punktnotation: (Adresse1.Vorname = “Peter“);
\item Pfeilnotation (->) wenn struct Pointer
\item Gesamtlänge der Struktur: sizeof(<Struktur>)
\item Weiteres hinzufügen von Komponenten während der Laufzeit nicht möglich.
\item Cross-Model Pseudo-Labeling
\item Primary backbone
\item Supplemented by lightweight auxiliary network
\begin{itemize}
\item Different structure
\item Fewer channels
\end{itemize}
\item Different representation of data complements primary backbone
\end{itemize}
\end{frame}
%------------------------------------------------
\begin{frame}[fragile]{Strukturen als Funktionsargument}
Ohne Typedef:
\begin{lstlisting}
void testfunc(struct Adresse a){
long plz = a.plz;
}
\end{lstlisting}
Mit Typedef:
\begin{lstlisting}
void testfunc(Adr a){
long plz = a.plz;
}
\end{lstlisting}
\begin{frame}{Performance glance}
todo the pic of the performance graph
\end{frame}
%------------------------------------------------
\begin{frame}[fragile]{Strukturen in Java}
\begin{itemize}
\item existieren nicht
\item stattdessen Klassen
\end{itemize}
\begin{lstlisting}[language=java]
public class Adresse
{
String name;
String strasse;
short hausnummer;
long plz;
String stadt;
}
\end{lstlisting}
\end{frame}
%----------------------------------------------------------------------------------------
% SECTION 3
%----------------------------------------------------------------------------------------
\section{Anwendung} % Section title slide, unnumbered
%------------------------------------------------
\begin{frame}[fragile]{Struktur als Pointer}
\begin{lstlisting}
struct mystruct {
int data;
};
typedef struct MyStruct MyStruct;
void beispiel(MyStruct * str) {
int d = str->data;
int dd = (*str).data; // equivalent
}
int main(){
MyStruct struc;
struc.data = 5;
beispiel(&struc);
return 0;
}
\end{lstlisting}
\end{frame}
%------------------------------------------------
\begin{frame}[fragile]{Verkettete Listen}
\begin{lstlisting}
struct node {
int data;
struct node* next; /* Typ Node hier nicht moeglich
da erst spaeter definiert */
};
typedef struct node Node;
void beispiel() {
// Erstellen von root
Node *root = malloc(sizeof(Node));
root->data = 17;
// Anhaengen eines Knotens
Node *secondNode = malloc(sizeof(Node));
root->next = secondNode;
secondNode->data = 19;
}
\end{lstlisting}
\end{frame}
%------------------------------------------------
% --- THE END
\begin{frame}[focus]
Danke für eure Aufmerksamkeit!
Thanks for your Attention!
\end{frame}
%----------------------------------------------------------------------------------------
@ -321,7 +225,7 @@ void beispiel() {
\appendix
\begin{frame}{Quellen}
\begin{frame}{Sources}
\nocite{*} % Display all references regardless of if they were cited
\bibliography{sources}
\bibliographystyle{plain}