Variational quantum approximate support vector machine with inference transfer

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 run-time co...

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Vydané v:	Scientific reports Ročník 13; číslo 1; s. 3288 - 10
Hlavní autori:	Park, Siheon, Park, Daniel K., Rhee, June-Koo Kevin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 25.02.2023 Nature Publishing Group Nature Portfolio
Predmet:	639/705/1042 639/766/259 639/766/483/481 Algorithms Bias Classification Computers Datasets Humanities and Social Sciences Machine learning multidisciplinary Random access memory Science Science (multidisciplinary) Support vector machines
ISSN:	2045-2322, 2045-2322
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