Understanding Autoencoders with Information Theoretic Concepts

30 Mar 2018Shujian YuJose C. Principe

Despite their great success in practical applications, there is still a lack of theoretical and systematic methods to analyze deep neural networks. In this paper, we illustrate an advanced information theoretic methodology to understand the dynamics of learning and the design of autoencoders, a special type of deep learning architectures that resembles a communication channel... (read more)

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