Meta-Learning: Learning to Learn Fast
Read OriginalThis article explores meta-learning, a subfield of machine learning focused on creating models that can learn new concepts or skills rapidly from a few examples, similar to human learning. It defines the problem, discusses its goals in supervised learning contexts like few-shot classification, and explains the training process where models are optimized over a distribution of tasks to perform well on unseen ones.
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