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diff --git a/notes/extensions.tex b/notes/extensions.tex index dd9933a..cc247ef 100644 --- a/notes/extensions.tex +++ b/notes/extensions.tex @@ -31,7 +31,11 @@ network learning however, we can place more informative priors. We can \item Take into account common graph structures, such as triangles \end{itemize} -We can sample from the posterior by MCMC. +We can sample from the posterior by MCMC. This might not be a very fast solution +however. In the case of the independent cascade model, there is an easier +solution: we can use the EM algorithm to compute the posterior, by using the +parent that \emph{does} infect us (if at all) as the latent variable in the +model. \subsection{Active Learning} |