In fact, for popular learning techniques including EM for HMMs (Rabiner, 1989) and variational EM for LDA (Wolfe et al., 2008), it can be shown that the parameter updates are independent of how the corpus is partitioned.
for those approaches our partitioning is guaranteed to produce the same models as any other partitioning method; i.e., model accuracy is unchanged.