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@@ -79,12 +79,12 @@ 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 arbitrary
-covariance matrices $R$ can be found in Section~\ref{sec:ext}.
+covariance matrices $R$ can be found in Appendix~\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 $S\subset T$.
-\subsection{Budget-Feasible Experimental Design: Full Information Case}
+\subsection{Budget-Feasible Experimental Design: Full Information Case}\label{sec:fullinfo}
Beyond the cardinality constraint in classical experimental design discussed above, a
budgeted version can also be considered.