From c9f0053f279a7899c838aa9640d2643a4f6bbcf8 Mon Sep 17 00:00:00 2001
From: Thibaut Horel <thibaut.horel@gmail.com>
Date: Sun, 1 Feb 2015 17:49:31 -0500
Subject: Abstract: provide -> prove

---
 paper/sections/abstract.tex | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'paper/sections/abstract.tex')

diff --git a/paper/sections/abstract.tex b/paper/sections/abstract.tex
index 9136be7..ad5b893 100644
--- a/paper/sections/abstract.tex
+++ b/paper/sections/abstract.tex
@@ -6,5 +6,5 @@ provided that the number of measurements is $\Omega(s\log m)$ where $s$ is the
 maximum degree of the graph and $m$ is the number of nodes.
 Furthermore, we show that our algorithm also recovers the edge weights (the
 parameters of the diffusion process) and is robust in the context of
-approximate sparsity. Finally we provide an almost matching lower bound of
+approximate sparsity. Finally we prove an almost matching lower bound of
 $\Omega(s\log\frac{m}{s})$.
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