Few-shot Learning

Sat, 18 Jul 2026 09:40:59 +0000

Definition

Few-shot learning aims to enable models to generalize from just a handful of examples, mimicking human learning efficiency. It typically relies on meta-learning strategies, where a model is trained on a variety of tasks to acquire the ability to quickly adapt to new tasks with minimal data. This is crucial in domains where labeled data is scarce or expensive to obtain, such as rare disease diagnosis or niche industrial defect detection.

ML Theory on English AI Terms Dictionary

Few-shot Learning

Definition