model-agnostic meta-learning
E1684185
UNEXPLORED
Model-agnostic meta-learning is a general optimization-based meta-learning framework that trains models to rapidly adapt to new tasks with minimal data, regardless of the underlying model architecture.
All labels observed (4)
| Label | Occurrences |
|---|---|
| MAML | 1 |
| Model-Agnostic Meta-Learning (MAML) | 1 |
| Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks | 1 |
| model-agnostic meta-learning canonical | 1 |
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: model-agnostic meta-learning
linked to: model-agnostic meta-learning
linked to: model-agnostic meta-learning