NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:3181
Title:Adaptive Gradient-Based Meta-Learning Methods

This paper addresses a new method for analyzing gradient-based meta-learning in the online setting, where the average regret-upper-bound analysis was presented. All of reviewers agree that a new theoretical framework in this paper has valuable contributions that can be applied to a variety of setting. While there were no further comments in the discussion period, I believe that the paper is deserved to be presented at NeurIPS.