Just as in our own paper , Domke took a decision-theoretic stance and proposed ERM as a way of calibrating the graphical model for use with approximate inference, or for use with data that do not quite match the modeling assumptions.
4 (Domke, 2011) is similar to (Stoyanov et al., 2011) in using ERMA to train model parameters to be used with "truncated" inference that will be run for only a fixed number of iterations.