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authorThibaut Horel <thibaut.horel@gmail.com>2015-12-11 18:00:43 -0500
committerThibaut Horel <thibaut.horel@gmail.com>2015-12-11 18:00:43 -0500
commitdeaa0d78822933f651005a8355120693d48a9d4a (patch)
tree129abcccd30b7c1ea725f4085852d953c4352bba /finale
parent8fd65558f9149d4161dbedad6d250dea30c1d239 (diff)
downloadcascades-deaa0d78822933f651005a8355120693d48a9d4a.tar.gz
Use accepted style, looks cleaner
Diffstat (limited to 'finale')
-rw-r--r--finale/final_report.tex32
-rw-r--r--finale/icml2015.sty5
2 files changed, 29 insertions, 8 deletions
diff --git a/finale/final_report.tex b/finale/final_report.tex
index 5f4e441..4203fa5 100644
--- a/finale/final_report.tex
+++ b/finale/final_report.tex
@@ -6,9 +6,13 @@
\usepackage[capitalize, noabbrev]{cleveref}
\usepackage{graphicx}
\usepackage{bbm}
-%\usepackage{fullpage}
+\usepackage{times}
+\usepackage{subfigure}
+\usepackage{natbib}
+\usepackage{algorithm}
+\usepackage{algorithmic}
\input{def}
-\usepackage{icml2015}
+\usepackage[accepted]{icml2015}
%\usepackage{algpseudocode}
\DeclareMathOperator*{\argmax}{arg\,max}
\DeclareMathOperator*{\argmin}{arg\,min}
@@ -38,12 +42,32 @@
\newtheorem*{example}{Example}
\newtheorem*{remark}{Remark}
-\title{Bayesian and Active Learning for Graph Inference}
+\title{}
\author{Thibaut Horel \and Jean Pouget-Abadie}
\begin{document}
-\maketitle
+\twocolumn[
+\icmltitle{Bayesian and Active Learning for Graph Inference}
+
+% It is OKAY to include author information, even for blind
+% submissions: the style file will automatically remove it for you
+% unless you've provided the [accepted] option to the icml2015
+% package.
+\icmlauthor{Thibaut Horel}{thorel@seas.harvard.edu}
+\icmladdress{Harvard University}
+\icmlauthor{Jean Pouget-Abadie}{jeanpougetabadie@g.harvard.edu}
+\icmladdress{Harvard University}
+
+% You may provide any keywords that you
+% find helpful for describing your paper; these are used to populate
+% the "keywords" metadata in the PDF but will not be shown in the document
+\icmlkeywords{Sparse Recovery, Cascade Models, Graph Inference, Networks,
+Diffusion Processes}
+
+\vskip 0.3in
+]
+
\begin{abstract}
The Network Inference Problem (NIP) is the machine learning challenge of
recovering the edges and edge weights of an unknown weighted graph from the
diff --git a/finale/icml2015.sty b/finale/icml2015.sty
index 4798e3c..4e78251 100644
--- a/finale/icml2015.sty
+++ b/finale/icml2015.sty
@@ -107,10 +107,7 @@
% final/accepted version of the ``appearing in'' note. Modify it to
% change that text.
%%%%%%%%%%%%%%%%%%%%
-\newcommand{\ICML@appearing}{\textit{Proceedings of the
-$\mathit{32}^{nd}$ International Conference on Machine Learning},
-Lille, France, 2015. JMLR: W\&CP volume 37.
-Copyright 2015 by the author(s).}
+\newcommand{\ICML@appearing}{}
%%%%%%%%%%%%%%%%%%%%
% This string is printed at the bottom of the page for the draft/under