Before revision: We consider making outputs of the greedy algorithm for monotone submodular function maximization differentiable w.r.t. parameters of objective functions  .
After revision: We consider making outputs of the greedy algorithm for monotone submodular function maximization differentiable w.r.t. parameters of objective functions ; this is motivated by many applications, e.g., sensitivity analysis and end-to-end learning .