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Diffstat (limited to 'problem.tex')
| -rw-r--r-- | problem.tex | 4 |
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 $S\subset T$. |