Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning

27 Mar 2020Andreas KirschClare LyleYarin Gal

The information bottleneck (IB) principle offers both a mechanism to explain how deep neural networks train and generalize, as well as a regularized objective with which to train models. However, multiple competing objectives have been proposed based on this principle, and the information-theoretic quantities in these objectives are difficult to compute for large deep neural networks... (read more)

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