You Don’t Need Many Labels to Learn
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A Gaussian Mixture Variational Autoencoder (GMVAE) can be trained entirely without labels and then converted into a classifier using as little as 0.2% labeled data — 35x less than XGBoost needs for comparable accuracy. The key insight is that unsupervised training already discovers the data's cluster structure; labels are only
Table of contents
IntroductionTurning Clusters Into a ClassifierHow Much Supervision Do We Need in Practice?ConclusionSort: