  We consider a general $p$-norm objective for experimental design problems
that captures some well-studied objectives (D/A/E-design) as special cases. We
prove that a randomized local search approach provides a unified algorithm to
solve this problem for all $p$. This provides the first approximation algorithm
for the general $p$-norm objective, and a nice interpolation of the best known
bounds of the special cases.
