  We study a simple model of unsupervised learning where the single symmetry
breaking vector has binary components $\pm 1$. We calculate exactly the
Bayes-optimal performance of an estimator which is required to lie in the same
discrete space. We also show that, except for very special cases, such an
estimator cannot be obtained by minimization of a class of variationally
optimal potentials.
