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authorjeanpouget-abadie <jean.pougetabadie@gmail.com>2014-12-07 16:20:40 -0500
committerjeanpouget-abadie <jean.pougetabadie@gmail.com>2014-12-07 16:20:40 -0500
commit4ba0141322e8d35da9a762909603bd280dec64bf (patch)
tree97b97530f13ab401ce4b6fc6704d0134adaad78a /notes
parent566f9248c05db44133e3cbf145a4cbaf2fed140d (diff)
downloadcascades-4ba0141322e8d35da9a762909603bd280dec64bf.tar.gz
bug fix: initialization to directed graph missing
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@@ -19,7 +19,9 @@ Given a set of observed cascades, the \textbf{graph reconstruction problem} cons
\section{Related Work}
-In previous work, this problem has been formulated in different ways, including a convex optimization and a maximum likelihood problem. However, there is no known algorithm for graph reconstruction with theoretical guarantees and with a reasonable required sample size.
+There have been several works tackling the graph reconstruction problem in variants of the independent cascade. We briefly summarize their results and approaches below.
+
+
\section{The Voter Model}
@@ -278,7 +280,6 @@ $\delta_4 = .54$ & $\delta_4 = .37$ & $\delta_4 = .43$ & $\delta_4 = .23$ \\
The results of our findings on a very small social network (a subset of the famous Karate club), show that as the number of cascades increase the RIP constants decrease and that if $p_\text{init}$ is small then the RIP constant decrease as well. Finally the constants we obtain are either under or close to the $.25$ mark set by the authors of \cite{candes}.
-
\subsection{Testing our algorithm}