  We investigate the sets of joint probability distributions that maximize the
average multi-information over a collection of margins. These functionals serve
as proxies for maximizing the multi-information of a set of variables or the
mutual information of two subsets of variables, at a lower computation and
estimation complexity. We describe the maximizers and their relations to the
maximizers of the multi-information and the mutual information.
