From MAML to MAML++

Author(s): Edward Ma

Originally published on Towards AI.

Training Instability:

Photo by Edward Ma on Unsplash

Imagine that you only see dog a few times, human beings are able to recognize a new concept or idea and recognizing dog later on. Meta-Learning is inspired by this idea, while Model-Agnostic Meta-Learning, aka MAML (Finn et al. 2017), is one of the breakthroughs in meta-learning research.

If you do not feel familiar with meta-learning or MAML (Finn et al. 2017), you may check the introduction to meta-learning and unsupervised learning in meta-learning stories. In short, meta-learning is designed to overcome the lack of training problems and handling unseen labels in prediction time. The objective… Read the full blog for free on Medium.

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Published via Towards AI