Learning an Explicit Hyperparameter Prediction Policy Conditioned on Tasks

This study interprets meta learning methodology as learning an explicit hyperparameter prediction policy shared by all training tasks, which guarantees that the meta-learned learning methodology is able to flexibly fit diverse query tasks, instead of only obtaining fixed hyperparameters by many current meta learning methods.