  We present a simple, yet useful result about the expected value of the
determinant of random sum of rank-one matrices. Computing such expectations in
general may involve a sum over exponentially many terms. Nevertheless, we show
that an interesting and useful class of such expectations that arise in, e.g.,
D-optimal estimation and random graphs can be computed efficiently via
computing a single determinant.
