A study on the similarities of Deep Belief Networks and Stacked Autoencoders

Andrea De Giorgio
Restricted Boltzmann Machines (RBMs) and autoencoders have been used-in several variants-for similar tasks, such as reducing dimensionality or extracting features from signals. Even though their structures are quite similar, they rely on different training theories. Lately, they have been largely used as building blocks in deep learning architectures that are called deep belief networks (instead of stacked RBMs) and stacked autoencoders. In light of this, the student has worked on this thesis with the aim...
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