Quantum Support Vector Machines and Quantum Kernel Methods

Quantum Support Vector Machines and Quantum Kernel Methods | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 25 August 2025 V1 Latest version Share on Quantum Support Vector Machines and Quantum Kernel Methods Authors : Li Xu , Jing Wang , Chen Jiang , Jiamin Xu , Ming Li 0000-0003-0835-9635 [email protected] , and Weishan Zhang Authors Info & Affiliations https://doi.org/10.22541/au.175615204.43126822/v1 Published Software: Practice and Experience Version of record Peer review timeline 369 views 313 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Machine learning algorithms and quantum computing have received widespread attention in recent years, and the combination of the two has given rise to quantum machine learning algorithms. Quantum machine learning algorithms have been accelerated by quantum computing in terms of computation, enabling them to process data more efficiently and quickly. Quantum support vector machine is a prominent representative in this field, which aims to efficiently classify data and has been a hot research direction in recent years. In this review, we provide an overview of recent progress of quantum support machine machines. Then we introduce two types of the multi-classification quantum support vector machines. Followed by the latest progress on quantum kernel methods. Supplementary Material File (review-qsvm.pdf) Download 3.82 MB Information & Authors Information Version history V1 Version 1 25 August 2025 Peer review timeline Published Software: Practice and Experience Version of Record 13 Apr 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords quantum algorithms quantum kernel quantum support vector machines Authors Affiliations Li Xu China University of Petroleum East China - Qingdao Campus View all articles by this author Jing Wang China University of Petroleum East China - Qingdao Campus View all articles by this author Chen Jiang Jinan Institute of Quantum Technology View all articles by this author Jiamin Xu Jinan Institute of Quantum Technology View all articles by this author Ming Li 0000-0003-0835-9635 [email protected] China University of Petroleum East China - Qingdao Campus View all articles by this author Weishan Zhang China University of Petroleum East China - Qingdao Campus View all articles by this author Metrics & Citations Metrics Article Usage 369 views 313 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Li Xu, Jing Wang, Chen Jiang, et al. Quantum Support Vector Machines and Quantum Kernel Methods. Authorea . 25 August 2025. DOI: https://doi.org/10.22541/au.175615204.43126822/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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