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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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
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Nature Portfolio
2021
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| Accès en ligne: | https://doaj.org/article/ab490becf52a484583c18e292dabe3d1 |
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