N-Shot Learning

N-SHOT LEARNING

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    ​Zero shot, one shot, few shot (siamese is one shot)

ZERO SHOT LEARNING

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    ​Instead of using class labels, we use some kind of vector representation for the classes, taken from a co-occurrence-after-svd or word2vec. - quite clever. This enables us to figure out if a new unseen class is near one of the known supervised classes. KNN can be used or some other distance-based classifier. Can we use word2vec for similarity measurements of new classes?
    Image by Dr. Timothy Hospedales, Yandex​
    for classification, we can use nearest neighbour or manifold-based labeling propagation.
    Image by Dr. Timothy Hospedales, Yandex Multiple category vectors? Multilabel zero-shot also in the video
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GPT3 is ZERO, ONE, FEW