A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints

In this paper, we consider an online optimization problem in which the reward functions are DR-submodular, and in addition to maximizing the total reward, the sequence of decisions must satisfy some convex constraints on average.