An empirical evaluation of deep architectures on problems with many factors of variation

  title={An empirical evaluation of deep architectures on problems with many factors of variation},
  author={H. Larochelle and D. Erhan and Aaron C. Courville and James Bergstra and Yoshua Bengio},
  booktitle={ICML '07},
Recently, several learning algorithms relying on models with deep architectures have been proposed. Though they have demonstrated impressive performance, to date, they have only been evaluated on relatively simple problems such as digit recognition in a controlled environment, for which many machine learning algorithms already report reasonable results. Here, we present a series of experiments which indicate that these models show promise in solving harder learning problems that exhibit many… 

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    Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.
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