Sparsely Activated Networks: A new method for decomposing and compressing data

30 Oct 2019Paschalis Bizopoulos

Recent literature on unsupervised learning focused on designing structural priors with the aim of learning meaningful features, but without considering the description length of the representations. In this thesis, first we introduce the{\phi}metric that evaluates unsupervised models based on their reconstruction accuracy and the degree of compression of their internal representations... (read more)

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