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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Kolejni autorzy:	Geiger, Bernhard (Redaktor), Kubin, Gernot (Redaktor)
Format:	Rozdział
Wydane:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Hasła przedmiotowe:	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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Information Bottleneck : Theory and Applications in Deep Learning

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