adding simple bayes function

1 files changed, 5 insertions, 1 deletions

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}