| Autor: |
Jonas Jäger, Roman V. Krems |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Nature Communications, Vol 14, Iss 1, Pp 1-7 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-023-36144-5 |
| Popis: |
Rigorous results about the real computational advantages of quantum machine learning are few. Here, the authors prove that a PROMISEBQP-complete problem can be expressed by variational quantum classifiers and quantum support vector machines, meaning that a quantum advantage can be achieved for all ML classification problems that cannot be classically solved in polynomial time. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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