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| -rw-r--r-- | paper/sections/abstract.tex | 2 |
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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 $\Omega(s\log\frac{m}{s})$. |