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This document discusses data-efficient machine learning techniques. It notes that while deep neural networks are powerful models, they require large amounts of labeled training data to avoid overfitting. However, recent advances in machine learning make it possible to learn from less data by taking a more generative approach. Generative models can leverage both labeled data containing inputs and outputs, as well as larger amounts of cheaper unlabeled input-only data, to discover hidden structures that impro

Author

foliox

Language

EN