Optimizing a polynomial function on a quantum processor
Abstract The gradient descent method is central to numerical optimization and is the key ingredient in many machine learning algorithms. It promises to find a local minimum of a function by iteratively moving along the direction of the steepest descent. Since for high-dimensional problems the requir...
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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/ee291d3fa219422aa4c45b7a814186f3 |
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