MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets

A recent technical breakthrough in the domain of machine learning is the discovery and the multiple applications of Generative Adversarial Networks (GANs). Those generative models are computationally demanding, as a GAN is composed of two deep neural networks, and because it trains on large datasets...

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Veröffentlicht in:	Proceedings - IEEE International Parallel and Distributed Processing Symposium S. 866 - 877
Hauptverfasser:	Hardy, Corentin, Le Merrer, Erwan, Sericola, Bruno
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.05.2019
Schlagworte:	Computational modeling Deep Learning Distributed Datasets Gallium nitride Generative Adversarial Network Generative adversarial networks Generators Machine learning Servers Training
ISSN:	1530-2075
Online-Zugang:	Volltext
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