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authorericbalkanski <ericbalkanski@MACD-01953.local>2014-12-07 15:16:18 -0500
committerericbalkanski <ericbalkanski@MACD-01953.local>2014-12-07 15:16:18 -0500
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treedbb7b3316c905cfa07afd5fba7e5a74fd34affa7 /notes/reportYaron.tex
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downloadcascades-aca5c88f9856c9cdd676e22e44e1955c3e75f676.tar.gz
Added examples to report
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+++ b/notes/reportYaron.tex
@@ -84,6 +84,42 @@ If the vector $\vec x_i$ is sufficiently sparse, i.e. node $i$ has sufficiently
\subsection{Example}
+
+\begin{figure}
+\centering
+\includegraphics[width=0.3\textwidth]{voter.png}
+\caption{A cascade in the voter model with time steps $t = 0,1,2$ over a graph with 5 vertices}
+\end{figure}
+
+
+
+
+To recover the neighbors of $v_1$, we get the following matrix $M$ for the example in Figure 1:
+
+\begin{align*}
+&\hspace{0.35cm} v_2 \hspace{0.2 cm} v_3 \hspace{0.2 cm} v_4 \hspace{0.2 cm} v_5 &\\
+\vspace{1 cm}
+M = & \left( \begin{array}{cccc}
+0 & 0 & 1 & 1 \\
+1 & 1 & 0 & 0 \\
+\end{array} \right) & \begin{array}{l} \hspace{ -4.5 cm}
+\text{time step 0} \\
+ \hspace{ - 4.5cm} \text{time step 1} \\
+\end{array}
+\end{align*}
+
+and the vector $b_1$:
+
+\begin{align*}
+b_1 = & \left( \begin{array}{c}
+1 \\
+1 \\
+\end{array} \right) & \begin{array}{l} \hspace{ - 5cm}
+\text{time step 1} \\
+ \hspace{ - 5cm} \text{time step 2} \\
+ \end{array}
+\end{align*}
+
\section{The Independent Cascade Model}
\subsection{Description}
@@ -127,6 +163,43 @@ e^{M_i \vec \theta_i} = 1 - \vec b_i + \vec \epsilon_i
Note that this is not exactly a sparse recovery model due to the non-linear exponential term. It is of the author's opinion however that if the probabilities $p_{j,i}$ are restrained to a bounded interval $[0, 1- \eta]$, then most of the results which hold for the linear voter model will continue to hold in this case.
+\subsection{Example}
+
+\begin{figure}
+\centering
+\includegraphics[width=0.3\textwidth]{icc.png}
+\caption{A cascade in the independent cascade model with time steps $t = 0,1,2$ over a graph with 5 vertices}
+\end{figure}
+
+
+
+To recover the neighbors of $v_5$, we get the following matrix $M$ for the example in Figure 2:
+\begin{align*}
+&v_1 \hspace{0.2 cm} v_2 \hspace{0.2 cm} v_3 \hspace{0.2 cm} v_4 \\
+\vspace{1 cm}
+M = & \left( \begin{array}{cccc}
+1 & 0 & 0 & 0 \\
+0 & 1 & 1 & 0 \\
+\end{array} \right) \begin{array}{l} \hspace{ 1cm}
+\text{time step 0} \\
+ \hspace{ 1cm} \text{time step 1} \\
+ \end{array}
+\end{align*}
+
+and the vector $b_5$:
+
+\begin{align*}
+b_5 = & \left( \begin{array}{c}
+0 \\
+1 \\
+\end{array} \right) \begin{array}{l} \hspace{ 1cm}
+\text{time step 1} \\
+ \hspace{ 1cm} \text{time step 2} \\
+ \end{array}
+\end{align*}
+
+
+
\section{Sparse Recovery}
\subsection{Introduction}