gibbs-erm learning is a natural idealized model of learning with stochastic
optimization algorithms (such as Stochastic Gradient Langevin Dynamics and
---to some extent--- Stochastic Gradient Descent), while it also arises in
other contexts, including PAC-Bayesian theory, and sampling