Learning Multiple Layers of Features from Tiny Images

  title={Learning Multiple Layers of Features from Tiny Images},
  author={Alex Krizhevsky},
Groups at MIT and NYU have collected a dataset of millions of tiny colour images from the web. It is, in principle, an excellent dataset for unsupervised training of deep generative models, but previous researchers who have tried this have found it dicult to learn a good set of lters from the images. We show how to train a multi-layer generative model that learns to extract meaningful features which resemble those found in the human visual cortex. Using a novel parallelization algorithm to… CONTINUE READING
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