zero-shot learning

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English

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Wikipedia

Noun

zero-shot learning (uncountable)

  1. (machine learning) A problem setup in machine learning, where, at test time, a learner observes samples from classes that were not observed during training and attempts to predict the class that they belong to, typically based on auxiliary information.
    Coordinate terms: few-shot learning, N-shot learning, one-shot learning