Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

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...