Many problems in fitting observations while satisfying rank order constraints, occur in contexts of learning, Lipschitz regularization and Isotonic regression (with or without fused Lasso). All these problems can be abstracted as a convex cost closure problem which is to minimize the cost of deviating from the observations while satisfying rank order constraints. Any feasible solution that...