= Sparse maximum eigenvalue
{title2=$\kappa_m^2$}
For a <design matrix> $X$ with $p$ columns, define $\kappa_m^2=\max_{|M|=m}\lambda_{\max}(X_M^TX_M/n)$ for $1\le m\le p$. Equivalently this bounds $\|Xv\|_2^2/(n\|v\|_2^2)$ for <vectors> supported on at most $m$ coordinates. These quantities are nondecreasing: extend the support of a maximizing <vector> by zero coordinates and use the variational characterization of the largest <eigenvalue>. Values at $m>p$, including infinity, require a separate convention.
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