  We consider the problem associated to recovering the block structure of an
Ising model given independent observations on the binary hypercube. This new
model, called the Ising blockmodel, is a perturbation of the mean field
approximation of the Ising model known as the Curie-Weiss model: the sites are
partitioned into two blocks of equal size and the interaction between those of
the same block is stronger than across blocks, to account for more order within
each block. We study probabilistic, statistical and computational aspects of
this model in the high-dimensional case when the number of sites may be much
larger than the sample size.
