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Deep Learning A-Z™: Autoencoders - Stacked Autoencoders

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Kirill Eremenko

The document discusses stacked denoising autoencoders and how they can be used to learn useful representations in a deep network by training each layer to reconstruct its input while adding noise corruption. It provides the title of a 2010 paper by Pascal Vincent et al. that presents stacked denoising autoencoders and a link to access the full paper, as well as a note about additional recommended reading on the topic.

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© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z Movie 1 Movie 2 Movie 3 Movie 4 Movie 5 Movie 6 Encoding Decoding Movie 1 Movie 2 Movie 3 Movie 4 Movie 5 Movie 6
© SuperDataScienceDeep Learning A-Z Encoding Decoding Movie 1 Movie 2 Movie 3 Movie 4 Movie 5 Movie 6 Movie 1 Movie 2 Movie 3 Movie 4 Movie 5 Movie 6 Encoding
© SuperDataScienceDeep Learning A-Z Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion By Pascal Vincent et al. (2010) Link: http://www.jmlr.org/papers/volume11/vincent10a/vincent10a.pdf Additional Reading:

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