Variational quantum approximate support vector machine with inference transfer

Variational quantum approximate support vector machine with inference transfer

Abstract A kernel-based quantum classifier is the most practical and influential quantum machine learning technique for the hyper-linear classification of complex data. We propose a Variational Quantum Approximate Support Vector Machine (VQASVM) algorithm that demonstrates empirical sub-quadratic ru...

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Dades bibliogràfiques
Autors principals: Siheon Park, Daniel K. Park, June-Koo Kevin Rhee
Format: Article
Idioma:English
Publicat: Nature Portfolio 2023-02-01
Col·lecció:Scientific Reports
Accés en línia:https://doi.org/10.1038/s41598-023-29495-y

Internet

https://doi.org/10.1038/s41598-023-29495-y

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