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...

Täydet tiedot

Tallennettuna:

Bibliografiset tiedot
Muut tekijät:	Geiger, Bernhard (Toimittaja), Kubin, Gernot (Toimittaja)
Aineistotyyppi:	Kirjan osa
Julkaistu:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Aiheet:	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
Linkit:	Get Fullteks DOAB: description of the publication
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

Internet

Get Fullteks
DOAB: description of the publication

3rd Floor Main Library

Saatavuus: 3rd Floor Main Library
Hyllypaikka:	A1234.567
Nide 1	Saatavissa

Information Bottleneck : Theory and Applications in Deep Learning

Internet

3rd Floor Main Library

Samankaltaisia teoksia