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| -rw-r--r-- | paper/sections/model.tex | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/paper/sections/model.tex b/paper/sections/model.tex index 5f03199..4cef131 100644 --- a/paper/sections/model.tex +++ b/paper/sections/model.tex @@ -32,8 +32,6 @@ linear models} (GLM) to define a generalized linear cascade. \big(1-f(\inprod{\theta_i}{X^{t}}\big)^{1-x_i} \end{displaymath} where $f:\mathbb{R}\to[0,1]$. -Let $f: \mathbb{R} \leftarrow \mathbb{R}$ be an inverse link function. Let ${\cal F}_{< t}$ be the filtration defined by $\{ X^0, X^1, \dots, X^{t-1} \}$. A \emph{generalized linear cascade} is defined as: -$$\mathbb{P}(X^t = 1|{\cal F}_{< t}) = \exp(blabla$$ \end{definition} It follows immediately from this definition that a generalized linear cascade @@ -44,7 +42,9 @@ satisfies the Markov property: \subsection{Examples} \label{subsec:examples} -In this section, we show that both the Independent Cascade Model and the Voter model are Generalized Linear Cascades. We discuss the Linear Threshold model in Section~\ref{sec:linear_threshold} +In this section, we show that both the Independent Cascade Model and the Voter +model are Generalized Linear Cascades. The Linear Threshold model will be +discussed in Section~\ref{sec:linear_threshold} \subsubsection{Independent Cascade Model} |