For discriminative log-linear model structure learning: (i) the gaussian prior was fixed to be very weak, serving only to keep the weights away from infinity (σ = 100) and (ii) the conjunction selection was restricted to correspond to a Bayes Net structure with no features for subsets of feature conjunctions.
the only difference between the class of our modified discriminative log-linear models and the class of models considered in (Pernkopf and Bilmes, 2005;Grossman and Domingos, 2004) is that we do not restrict the parameters to be interpretable as probabilities.