Are learned features already better than handcrafted features (eg RBM vs SIFT)?
How is a Restricted Boltzmann machine different from an Autoencoder? Aren't both of them learning high level features in an unsupervised manner? Similarly, how is a Deep Belief Network different from a network of stacked Autoencoders?