In particular, maxent models without priors use the parameters Λ that maximize where x j , y j are training data instances.
with a Gaussian prior we find In this case, a trained model does not satisfy the constraints expected[i] = observed [i], but, as Chen and Rosenfeld show, instead satisfies constraints instead of a model that matches the observed count, we get a model matching the observed count minus λi σ 2 i : in language modeling terms, this is "discounting."