Adaptive hyperparameter updating for training restricted Boltzmann machines on quantum annealers

Abstract Restricted Boltzmann Machines (RBMs) have been proposed for developing neural networks for a variety of unsupervised machine learning applications such as image recognition, drug discovery, and materials design. The Boltzmann probability distribution is used as a model to identify network p...

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Autores principales: Guanglei Xu, William S. Oates
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/ab490becf52a484583c18e292dabe3d1
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