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    Rights statement: This is the peer reviewed version of the following article: This is the peer reviewed version of the following article: Zhang, Y, Ni, Q. Recent advances in quantum machine learning. Quantum Engineering. 2020; 2:e34. https://doi.org/10.1002/que2.34 which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/que2.34 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

    Accepted author manuscript, 376 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Recent advances in quantum machine learning

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published
Article numbere34
<mark>Journal publication date</mark>20/03/2020
<mark>Journal</mark>Quantum Engineering
Issue number1
Volume2
Number of pages20
Publication StatusPublished
Early online date2/03/20
<mark>Original language</mark>English

Abstract

Machine learning is a branch of artificial intelligence, and it has been widely used in many science and engineering areas, such as data mining, natural language processing, computer vision, biological analysis, and so on. Quantum computer is considered as one of the most promising technologies of human beings in the near future. With the development of machine learning and quantum computing, researchers consider to combine these two aspects to gain more benefits. As a result, a novel interdisciplinary subject has emerged?quantum machine learning. This article reviews the state-of-the-art research of algorithms of quantum machine learning and shows a path of the research from the basic quantum information to quantum machine learning algorithms from the perspective of people in the field of computer science.

Bibliographic note

This is the peer reviewed version of the following article: This is the peer reviewed version of the following article: Zhang, Y, Ni, Q. Recent advances in quantum machine learning. Quantum Engineering. 2020; 2:e34. https://doi.org/10.1002/que2.34 which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/que2.34 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.