Reviews: Efficient Meta Learning via Minibatch Proximal Update

UPDATE: I'd like to thank the authors for their detailed response. In light of this response I have increased my score to a 7. Originality This paper presents Meta-MinibatchProx, an algorithm for model and algorithm agnostic meta learning that, unlike MAML and friends, comes with theoretical guarantees of convergence. To the best of my knowledge it is the first such algorithm to offer any convergence guarantees, and also has the potential to scale to very large problems. Quality Something I would like to have seen addressed explicitly in this paper is the distinction between what I will call the "finite" and "infinite" versions of MMP. The distinction here is related to the comment "Usually we are only provided with n observed tasks..." on line 135.