From 2a4664283998d5bf9c6615d251fd62c30001b73e Mon Sep 17 00:00:00 2001
From: Thibaut Horel <thibaut.horel@gmail.com>
Date: Mon, 5 Nov 2012 02:18:05 +0100
Subject: Fix missing references

---
 general.tex | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

(limited to 'general.tex')

diff --git a/general.tex b/general.tex
index 4f9aaad..550d6b7 100644
--- a/general.tex
+++ b/general.tex
@@ -79,13 +79,13 @@ The value function given by the information gain \eqref{general} is submodular.
 \end{lemma}
 
 \begin{proof}
-The theorem is proved in a slightly different context in \cite{guestrin}; we
+The theorem is proved in a slightly different context in \cite{krause2005near}; we
 repeat the proof here for the sake of completeness. Using the chain rule for
 the conditional entropy we get:
-\begin{displaymath}\label{eq:chain-rule}
+\begin{equation}\label{eq:chain-rule}
     V(S) = H(y_S) - H(y_S \mid \beta) 
     = H(y_S) - \sum_{i\in S} H(y_i \mid \beta)
-\end{displaymath}
+\end{equation}
 where the second equality comes from the independence of the $y_i$'s
 conditioned on $\beta$. Recall that the joint entropy of a set of random
 variables is a submodular function. Thus, our value function is written in
-- 
cgit v1.2.3-70-g09d2

