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| author | jeanpouget-abadie <jean.pougetabadie@gmail.com> | 2015-05-18 10:51:49 +0200 |
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| committer | jeanpouget-abadie <jean.pougetabadie@gmail.com> | 2015-05-18 10:51:49 +0200 |
| commit | f3f40d2afed90aa220d90a28efbb82c860587057 (patch) | |
| tree | 172af44ddddb1c6da349776039aa4fd9fa63fce9 | |
| parent | 48a2579659a5cdb16fc65b5acda5722257cf4964 (diff) | |
| download | cascades-f3f40d2afed90aa220d90a28efbb82c860587057.tar.gz | |
fixed typo
| -rw-r--r-- | paper/sections/intro.tex | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/paper/sections/intro.tex b/paper/sections/intro.tex index f369e3c..7688aeb 100644 --- a/paper/sections/intro.tex +++ b/paper/sections/intro.tex @@ -133,8 +133,8 @@ the recovery of the graph's edges and the estimation of the model's parameters, and achieve close to optimal bounds. The work of~\cite{du2014influence} is slightly orthogonal to ours since they -suggest learning the \emph{influence} function, rather than the networks -parameters directly. +suggest learning the \emph{influence} function, rather than the +parameters of the network directly. %\begin{comment} %Their work has the merit of studying a generalization of the discrete-time %independent cascade model to continuous functions. Similarly to |