Large-scale deep unsupervised learning using graphics processors

  title={Large-scale deep unsupervised learning using graphics processors},
  author={Rajat Raina and Anand Madhavan and Andrew Y. Ng},
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free parameters. We consider two well-known unsupervised learning models, deep belief networks (DBNs) and sparse coding, that have recently been applied to a flurry of machine learning applications (Hinton & Salakhutdinov, 2006; Raina et al., 2007). Unfortunately, current learning algorithms for both models are too slow for large… CONTINUE READING
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