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Diffstat (limited to 'notes')
| -rw-r--r-- | notes/formalisation.pdf | bin | 197923 -> 198927 bytes | |||
| -rw-r--r-- | notes/formalisation.tex | 12 |
2 files changed, 2 insertions, 10 deletions
diff --git a/notes/formalisation.pdf b/notes/formalisation.pdf Binary files differindex 2d64bb0..daa0d6f 100644 --- a/notes/formalisation.pdf +++ b/notes/formalisation.pdf diff --git a/notes/formalisation.tex b/notes/formalisation.tex index 00eb891..3d20261 100644 --- a/notes/formalisation.tex +++ b/notes/formalisation.tex @@ -95,18 +95,10 @@ $$1 - \delta_T \leq \| M_T c \|_2^2 \leq 1 + \delta_T$$ For small $\delta_T$, the above equation defines a `loose' orthonormality property for the columns of $M$. -\section{Voter Model} -\subsection{The Model} - -Recap on what the model is +\section{Warm up: the voter model} -\subsection{Formulating the sparse recovery problem} +In the voter model, there are two types of nodes, {\it red} and {\it blue}. At every turn, each node $u$ chooses one of its neighbors uniformly (with probability $\frac{1}{deg(u)}$) and adopts the color of that neighbor. In most cases, we consider that the graphs includes self-loops, meaning the node has the option to keep his color for the next round. We fix a horizon $T$, and a set of {\it blue} nodes, and we observe the evolution of set of $red$ nodes. -\subsection{Results under strong assumptions} - -\subsection{Results under RIP condition} - -\subsection{Results under isotropic condition} \section{Independent Cascade Model} |