Information Bottleneck : Theory and Applications in Deep Learning

Information Bottleneck : Theory and Applications in Deep Learning

The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: • provide novel insights in...

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Bibliographic Details
Other Authors: Geiger, Bernhard (Editor), Kubin, Gernot (Editor)
Format: Book Chapter
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Information technology industries
information theory
variational inference
machine learning
learnability
information bottleneck
representation learning
conspicuous subset
stochastic neural networks
mutual information
neural networks
information
bottleneck
compression
classification
optimization
classifier
decision tree
ensemble
deep neural networks
regularization methods
information bottleneck principle
deep networks
semi-supervised classification
latent space representation
hand crafted priors
learnable priors
regularization
deep learning
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