Self-Supervised Learning

NPID (Non-Parametric Instance Discrimination) is a self-supervision approach that takes a non-parametric classification approach. Noise contrastive estimation is used to learn representations. Specifically, distances (similarity) between instances are calculated directly from the features in a non-parametric way.

Source: Unsupervised Feature Learning via Non-Parametric Instance Discrimination


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