a7a3d70c6d17a73140918996d03c014f-AuthorFeedback.pdf

NSL is theoretically connected with [Implicit Regularization in Matrix Factorization,5 NeurIPS 2017] which shows that factorized learning is biased towards the minimum nuclear norm solution. Weagree with the reviewer that our method can be viewed asan22 architectural modification which is generally useful. We use a simple way to construct a dynamic network whose23 equivalent weights are dependent on the input. In fact, meta-learning is just one of the suitable applications for our24 approach. We con-27 duct allthemeta-learning experiments28 requested by the reviewer.