Review for NeurIPS paper: Continual Learning in Low-rank Orthogonal Subspaces

Weaknesses: Despite having a novel core idea, I think this paper is not ready for publication and needs substantial improvement before publication: 1. Currently it seems that you need to know T because projection matrices P_t should be constructed before starting continual learning. This is a huge limitation because the very notion of "continual learning" implies that T is not known a priori because the learning agent supposedly is learning over unlimited time periods (i.e., we may even have T\rightarrow\infty) . Currently, learning task T 1 is going to invalidate your core idea because building an orthogonal P_{T 1} does not seem to be trivial. In my opinion, this constraint should be removed. But I think this is a highly slippery assumption.