Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
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We explore an original strategy for building deep networks, based on stacking layers of denoising autoencoders which are trained locally to denoise corrupted versions of their inputs. The resulting...