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Supervised learning with quantum computers

Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at pr...

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Detalles Bibliográficos
Autores principales: Schuld, Maria, Petruccione, Francesco
Lenguaje:eng
Publicado: Springer 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-96424-9
http://cds.cern.ch/record/2638878
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author Schuld, Maria
Petruccione, Francesco
author_facet Schuld, Maria
Petruccione, Francesco
author_sort Schuld, Maria
collection CERN
description Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
publisher Springer
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spelling cern-26388782021-04-21T18:43:10Zdoi:10.1007/978-3-319-96424-9http://cds.cern.ch/record/2638878engSchuld, MariaPetruccione, FrancescoSupervised learning with quantum computersComputing and ComputersQuantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.Springeroai:cds.cern.ch:26388782018
spellingShingle Computing and Computers
Schuld, Maria
Petruccione, Francesco
Supervised learning with quantum computers
title Supervised learning with quantum computers
title_full Supervised learning with quantum computers
title_fullStr Supervised learning with quantum computers
title_full_unstemmed Supervised learning with quantum computers
title_short Supervised learning with quantum computers
title_sort supervised learning with quantum computers
topic Computing and Computers
url https://dx.doi.org/10.1007/978-3-319-96424-9
http://cds.cern.ch/record/2638878
work_keys_str_mv AT schuldmaria supervisedlearningwithquantumcomputers
AT petruccionefrancesco supervisedlearningwithquantumcomputers