Meta-Learning in Neural Networks: A Survey 笔记

这篇survey解决了我的那些疑惑？

1. meta learning 的动机是什么：generalization performance or learning speed of the inner algorithm.

2. Feed-forward-model(FFM)如何理解：Here ω is the hypernetwork and it synthesises θ given the source dataset in a feed-forward pass，.
3. Main challenges and Chance of meta learning: diverse task distributions (In vanilla multi-task learning, this phenomenon is relatively well studied with, e.g., methods that group tasks into clusters or subspaces. However this is only just beginning to be explored in meta-learning)

我的疑惑：

是meta learning 成就了few shot learning，还是few shot learning 成就了meta learning?