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diff --git a/paper/sections/experiments.tex b/paper/sections/experiments.tex index 7336f93..58077a7 100644 --- a/paper/sections/experiments.tex +++ b/paper/sections/experiments.tex @@ -9,7 +9,7 @@ %graphs, nbr of measurements vs.~number of cascades. One common metric for all %types of graphs (possibly the least impressive improvement)} -\begin{table*}[t] +\begin{figure*}[t] \centering \begin{tabular}{l l l} \hspace{-0.5em}\includegraphics[scale=.28]{figures/barabasi_albert.pdf} @@ -27,7 +27,7 @@ ($\ell_2$-norm \emph{vs.} $n$) & (f) Watts-Strogatz (F$1$ \emph{vs.} $p_{\text{init}}$) \end{tabular} -\captionof{figure}{Figures (a) and (b) report the F$1$-score in $\log$ scale for +\caption{Figures (a) and (b) report the F$1$-score in $\log$ scale for 2 graphs as a function of the number of cascades $n$: (a) Barabasi-Albert graph, $300$ nodes, $16200$ edges. (b) Watts-Strogatz graph, $300$ nodes, $4500$ edges. Figure (c) plots the Precision-Recall curve for various values @@ -37,7 +37,7 @@ graph which is: (d) exactly sparse (e) non-exactly sparse, as a function of the number of cascades $n$. Figure (f) plots the F$1$-score for the Watts-Strogatz graph as a function of $p_{init}$.}~\label{fig:four_figs} \vspace{-2em} -\end{table*} +\end{figure*} In this section, we validate empirically the results and assumptions of Section~\ref{sec:results} for varying levels of sparsity and different |