Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace

摘要

Gradient-based meta-learning methods leverage gradient descent to learn the commonalities among various tasks. While previous such methods have been successful in meta-learning tasks, they resort to simple gradient descent during meta-testing. Our primary contribution is the