Merge pull request #12 from kashefy/pca

Kernel PCA and layout fix for Online PCA
kashefy · May 6, 2020 · 95d8d87 · 95d8d87
2 parents bf183f5 + 01c452c
commit 95d8d87
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diff --git a/latex/headerMIslides.tex b/latex/headerMIslides.tex
@@ -28,6 +28,27 @@
 \tikzset{myrect/.style={rectangle, fill=#1!20, draw=#1!75, text=black}}
 \tikzstyle{axes}=[]
 
+% sticky note
+\usepackage{xparse}
+\usetikzlibrary{shadows}
+\definecolor{myyellow}{RGB}{242,226,149}
+\NewDocumentCommand\StickyNote{O{6cm}mO{6cm}}{%
+\begin{tikzpicture}
+\node[
+drop shadow={
+  shadow xshift=2pt,
+  shadow yshift=-4pt
+},
+inner xsep=7pt,
+fill=myyellow,
+xslant=0.05,
+yslant=-0.05,
+inner ysep=10pt
+]
+{\parbox[t][#1][c]{#3}{#2}};
+\end{tikzpicture}%
+}
+
 % from tex.stackexchange useful to align substacks
 
 \makeatletter

diff --git a/notes/02_online-pca/2_apply-online-pca.tex b/notes/02_online-pca/2_apply-online-pca.tex
@@ -44,14 +44,14 @@ \subsection{Novelty filter}
 }
 }
 
+\notesonly{- Yes by using the \emph{Anti-Hebbian rule}}
+
 \end{frame}
 
-\subsubsecname{Novelty Filter with normalization}
+\subsubsection{Novelty Filter with normalization}
 
 \begin{frame}\frametitle{\subsubsecname}
 
-\notesonly{- Yes by using the}
-
 	\begin{block}{Anti-Hebbian rule:}
 				\begin{equation}
 				\Delta w_j = \overbrace{-}^{\substack{	\text{``Anti''-} \\ \text{Hebbian} }} \varepsilon y^{(\alpha)} x_j^{(\alpha)}
@@ -200,7 +200,7 @@ \section{PCA vs. online PCA}
 \only<2>{
 \slidesonly{
 \begin{center}
-	\includegraphics[width=0.2\textwidth]{img/mem_pca_vs_online_pca}%
+	\includegraphics[width=0.2\textwidth]{img/meme_pca_vs_online_pca}%
 \end{center}
 }
 }

diff --git a/notes/02_online-pca/Makefile b/notes/02_online-pca/Makefile
@@ -12,6 +12,7 @@ slides: $(projname).slides.tex $(projname).tex
 	$(compile) $(projname).slides.tex
 	bibtex $(projname).slides
 	$(compile) $(projname).slides.tex
+	$(compile) $(projname).slides.tex
 #	$(compile) --interaction=batchmode   $(projname).slides.tex
 	mv $(projname).slides.pdf $(targetname).slides.pdf 
 
@@ -24,6 +25,7 @@ notes: $(projname).notes.tex $(projname).tex
 	$(compile) $(projname).notes.tex
 	bibtex $(projname).notes
 	$(compile) $(projname).notes.tex
+	$(compile) $(projname).notes.tex
 #	$(compile) --interaction=batchmode  $(projname).notes.tex
 	mv $(projname).notes.pdf $(targetname).notes.pdf 
 

diff --git a/...online-pca/img/mem_pca_vs_online_pca.jpeg → ...nline-pca/img/meme_pca_vs_online_pca.jpeg b/...online-pca/img/mem_pca_vs_online_pca.jpeg → ...nline-pca/img/meme_pca_vs_online_pca.jpeg
diff --git a/notes/03_kernel-pca/0_recap.tex b/notes/03_kernel-pca/0_recap.tex
@@ -0,0 +1,42 @@
+
+\section{linear PCA: Recap}
+
+\begin{frame}\frametitle{\secname}
+\begin{itemize}
+\item Requires \pause
+
+ centering the data.
+\only<2>{
+\slidesonly{
+\begin{center}
+	\includegraphics[width=0.2\textwidth]{img/mem_notthisagain}%
+\end{center}
+}
+}
+
+\pause
+
+\item Eigenvalue problem: $\vec C\,\vec e = \lambda \vec e$
+\item limited to \underline{linear} correlations
+\end{itemize}
+
+
+\begin{center}
+	\includegraphics[width=0.5\textwidth]{img/scatter}%
+	\captionof{figure}{linear vs. non-linear correlations}
+\end{center}
+
+Kernel PCA for finding non-linear features.\\
+
+
+\end{frame}
+
+\begin{frame}\frametitle{What is Kernel PCA about?}
+
+Don't panic! Kernel PCA is essentially standard linear PCA applied to a non-linearly transformed version of the data.
+
+\begin{center}
+	\includegraphics[width=0.3\textwidth]{img/koffer}%
+\end{center}
+
+\end{frame}