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Deep neural networks have recently shown impressive performance in several machine learning tasks. An important approach to training deep networks, useful especially when labeled data is scarce, relies on unsupervised pretraining of hidden layers followed by supervised finetuning. One of the most widely used approaches to unsupervised pretraining is to train each layer with the Contrastive Divergence...