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+\documentclass{sig-alternate-2013}
+
+
+\permission{Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage, and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Copyright is held by the author/owner(s).}
+\conferenceinfo{WWW 2015 Companion,}{May 18--22, 2015, Florence, Italy.}
+\copyrightetc{ACM \the\acmcopyr}
+\crdata{978-1-4503-3473-0/15/05. \\
+http://dx.doi.org/10.1145/2740908.2744107}
+
+\clubpenalty=10000
+\widowpenalty = 10000
+
+\title{Inferring Graphs from Cascades:\\ A Sparse Recovery Framework}
+\subtitle{[Extended Abstract]
+%\titlenote{A full version of this paper is available as \textit{Author's Guide to Preparing ACM SIG Proceedings Using \LaTeX$2_\epsilon$\ and BibTeX} at \texttt{www.acm.org/eaddress.htm}}}
+
+\numberofauthors{2}
+\author{
+\alignauthor
+Jean Pouget-Abadie\\
+       \affaddr{Harvard University}\\
+       \email{pougetabadie@g.harvard.edu}
+\alignauthor
+Thibaut Horel\\
+       \affaddr{Harvard University}\\
+       \email{thorel@seas.harvard.edu}
+}
+
+\begin{document}
+
+\maketitle
+
+\begin{abstract}
+\end{abstract}
+
+\category{I.2.6}{Artificial Intelligence}{Learning}[Parameter Learning]
+\terms{Theory, Performance, Measurements}
+\keywords{Graph Inference; Cascades; Sparse Recovery}
+
+
+%\section{Acknowledgments}
+
+%\bibliographystyle{abbrv}
+%\bibliography{sigproc}
+
+%\balancecolumns
+\end{document}