Ah, I'd always thought of EM as iterating over the parameters given a model, but I suppose it makes sense to see it as a search for a model, including parameters, that fits the data. Cool.
I'm fairly knowledgeable about Bayesian statistics, but I can't tell which technique you're referring to. It vaguely sounds like maximum likelihood, but ML doesn't iterate the model or priors. Could you explain further and give a reference?