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Adaptive hyperparameter updating for training restricted Boltzmann machines on quantum annealers
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 parameters...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851404/ https://www.ncbi.nlm.nih.gov/pubmed/33526868 http://dx.doi.org/10.1038/s41598-021-82197-1 |