NeurIPS 2020

Continuous Meta-Learning without Tasks

Meta Review

This paper addresses a continual meta-learning using unsegmented supervised tasks, which is quite a challenging and timely topic. All reviewers agree that the proposed method, referred to as MOCA, is a sound solution. The integration of Bayesian change point detection with meta-learning is an interesting idea. During the discussion period, one reviewer raised his/her score by one.