X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/presentation_reservoir.git/blobdiff_plain/0f62d4cc7837ade5e2b5f34a3d09a910bd211511..4196be5e022044fd7b16f0dd92a7337472a24c1f:/reservoir.tex

diff --git a/reservoir.tex b/reservoir.tex
index 48ecec8..950da0f 100644
--- a/reservoir.tex
+++ b/reservoir.tex
@@ -176,7 +176,7 @@ Application on the MNIST problem}
     \begin{enumerate}
     \item Pre-processing
       \begin{itemize}
-      \item Input data formating (1D~vector; sampling period $\rightarrow \delta \tau$)
+      \item Input data formatting (1D~vector; sampling period $\rightarrow \delta \tau$)
       \item $W^I$ initialization (randomly; normalization)
       \end{itemize}
     \item Concatenation of 1D~vectors $\rightarrow$ batch processing
@@ -210,24 +210,39 @@ Application on the MNIST problem}
     \item Different regression tests are also independent
     \end{itemize}
   \end{femtoBlock}
-  \smallskip
+\end{frame}
+
+\begin{frame}{Parallelization Scheme} % Slide 9
   \begin{femtoBlock}
     {In practice\\}
     \begin{itemize}
     \item Simulation code rewritten in C++
-    \item {\bf M}essage~{\bf P}assing~{\bf I}nterface~for~InterProcess~Communication
+    \item Eigen C++ library for linear algebra operations
+    \item InterProcess~Communication \\
+      $\rightarrow$ {\bf M}essage~{\bf P}assing~{\bf I}nterface
     \end{itemize}
   \end{femtoBlock}
   \smallskip
   \begin{femtoBlock}
-    {Test of new idea?\\}
+    {Performance on speech recognition problem\\}
+    \begin{itemize}
+    \item Same WER $\rightarrow$ similar classification accuracy
+    \item Reduced computation time
+    \end{itemize}
+    \centering
+    \vspace{0.125cm}
+    {\bf We can study problems with huge Matlab computation time}
+  \end{femtoBlock}
+  \medskip
+  \begin{femtoBlock}
+    {Testing a new idea?\\}
     \vspace{0.25cm}
     \centering
     First test with Matlab and then adapt to C++ with MPI
   \end{femtoBlock}
 \end{frame}
 
-\begin{frame}{Finding Optimal Parameters} % Slide 9
+\begin{frame}{Finding Optimal Parameters} % Slide 10
   % 1 - Quels parametres et pourquoi ?
   \begin{femtoBlock}
     {What parameters can be optimized?\\}
@@ -241,7 +256,7 @@ Application on the MNIST problem}
     \item Next
       \begin{itemize}
       \item Number of nodes significantly improving the solution (threshold)
-      \item Input data filter (convolutional filter for images)
+      \item Input data filter (convolution filter for images)
       \end{itemize}
     \end{itemize}
     \centering
@@ -253,53 +268,104 @@ Application on the MNIST problem}
     \begin{itemize}
     \item Currently $\rightarrow$ simulated annealing \\
       {\small (probabilistic global search controlled by a cooling schedule)}
-    \item Next $\rightarrow$ other metaheuristics like evolutionay algorithms
+    \item Next $\rightarrow$ other metaheuristics like evolutionary algorithms
     \end{itemize}
   \end{femtoBlock}
 \end{frame}
 
-\begin{frame}{Performances of the parallel code} % Slide 10
+\section{Performances on the MNIST problem}
+
+\begin{frame}{Application on the MNIST problem} % Slide 11
   \begin{femtoBlock}
-    {Speech recognition problem\\}
+    {Task of handwritten digits recognition\\}
+    \centering
+    \vspace{0.125cm}
+    National Institute of Standards and Technology database
     \begin{itemize}
-    \item Same WER $\rightarrow$ similar classification accuracy
-    \item Reduced computation time $\rightarrow$ speedup...
+    \item Training dataset $\rightarrow$ american census bureau employees
+    \item Test dataset $\rightarrow$ american high school students
     \end{itemize}
+  \end{femtoBlock}
+  \smallskip
+  \begin{femtoBlock}
+    {Mixed-NIST database is widely used in machine learning\\}
     \centering
-    \vspace{0.25cm}
-    We can study problems with huge Matlab computation time
+    \vspace{0.125cm}
+    Mixing of both datasets and improved images
+    \begin{columns}
+      \begin{column}{7.5cm}
+        \begin{itemize}
+        \item Datasets
+          \begin{itemize}
+          \item Training $\rightarrow$ 60,000 samples
+          \item Test $\rightarrow$ 10,000 samples
+          \end{itemize}
+        \item Grayscale Images      
+          \begin{itemize}
+          \item Normalized to fit into a $20\times20$ pixel bounding box
+          \item Centered and anti-aliased
+          \end{itemize}
+        \end{itemize}
+      \end{column}
+      \begin{column}{3cm}
+        \centering
+        \includegraphics[width=3cm]{mnist.png}
+      \end{column}
+    \end{columns}
   \end{femtoBlock}
+  % 1 - Decrire ce qu'est le MNIST
+  % 2 - Setup de notre reservoir
 \end{frame}
 
-\section{Performances on the MNIST problem}
+\begin{frame}{Performances of the parallel code} % Slide 12
+  % To be completed
+  10000 images:\\
+  1000 reservoirs of 2 neurons, error : 3.85\%\\
+  1 reservoir of 2000 neurons, error : 7.14\%
+  \includegraphics[width=7.5cm]{speedup.pdf}
+\end{frame}
 
-\begin{frame}{Application on the MNIST problem} % Slide 12
-  % 1 - Decrire ce qu'est le MNIST
-  % 2 - Setup de notre reservoir
+\begin{frame}{Exploring ways to improve the results} % Slide 13
+  % Tableau recapitulant les performances
 \end{frame}
 
-\begin{frame}{Comparison with other approaches} % Slide 13
+\begin{frame}{Comparison with other approaches} % Slide 14
   % 1 - Convolutional Neural Networks
   % 2 - Reservoir en pipeline (papier de 2015)
 \end{frame}
 
-\begin{frame}{Comparison with other approaches} % Slide 14
+\begin{frame}{Comparison with other approaches} % Slide 15
   % Tableau recapitulant les performances
 \end{frame}
 
 \section{Conclusion and perspectives}
 
-\begin{frame}{Conclusion and perspectives} % Slide 15
-
-
-  Many perspectives (we are just beginning)
-  Improvement of the code\\
-  Test of many ideas : number of comities\\
-  One reservoir to learn and another one to learn error and correct
-  them\\
-  Test other large problems in simulation before in real\\
-  => Try to test many configuration and to find optimal parameters
-  
+\begin{frame}{Conclusion and perspectives} % Slide 16
+  \begin{femtoBlock}
+    {Results\\}
+    \begin{itemize}
+    \item A parallel code allowing fast simulations
+    \item An evaluation on the MNIST problem
+    \end{itemize}
+  \end{femtoBlock}
+  \begin{femtoBlock}
+    {Future works\\}
+    \begin{itemize}
+    \item Further code improvement
+    \item Use of several reservoirs
+      \begin{itemize}
+      \item Committees
+      \item Correct errors of a reservoir by another one
+      \end{itemize}
+    \end{itemize}
+  \end{femtoBlock}
+  %Many perspectives (we are just beginning)
+  %Improvement of the code\\
+  %Test of many ideas : number of comities\\
+  %One reservoir to learn and another one to learn error and correct
+  %them\\
+  %Test other large problems in simulation before in real\\
+  %=> Try to test many configuration and to find optimal parameters
 \end{frame}
 
 \begin{frame}{Thank you for your attention}
