general

1 files changed, 2 insertions, 2 deletions

diff --git a/problem.tex b/problem.tex
index 536481a..d505280 100644
--- a/problem.tex
+++ b/problem.tex
@@ -77,8 +77,8 @@ prior covariance is the identity matrix, \emph{i.e.}, $R=I_d\in \reals^{d\times
 d}.$ Intuitively, this corresponds to the simplest prior, in which no direction
 of $\reals^d$ is a priori favored; equivalently, it also corresponds to the
 case where ridge regression estimation \eqref{ridge} performed by $\E$ has
-a penalty term $\norm{\beta}_2^2$. A generalization of our results to general
-matrices $R$ can be found in Section~\ref{sec:ext}.
+a penalty term $\norm{\beta}_2^2$. A generalization of our results to arbitrary 
+covariance matrices $R$ can be found in Section~\ref{sec:ext}.
 
  %Note that \eqref{dcrit} is a submodular set function, \emph{i.e.}, 
 %$V(S)+V(T)\geq V(S\cup T)+V(S\cap T)$ for all $S,T\subseteq \mathcal{N}$; it is also monotone, \emph{i.e.}, $V(S)\leq V(T)$ for all $S\subset T$.