{"id":"https://openalex.org/W3169581362","doi":"https://doi.org/10.1109/tnnls.2021.3084467","title":"Quantum-Inspired Support Vector Machine","display_name":"Quantum-Inspired Support Vector Machine","publication_year":2021,"publication_date":"2021-06-10","ids":{"openalex":"https://openalex.org/W3169581362","doi":"https://doi.org/10.1109/tnnls.2021.3084467","mag":"3169581362","pmid":"https://pubmed.ncbi.nlm.nih.gov/34111003"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3084467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3084467","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101949226","display_name":"Chen Ding","orcid":"https://orcid.org/0000-0003-2227-2923"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210124140","display_name":"CAS Key Laboratory of Urban Pollutant Conversion","ror":"https://ror.org/02w5xy446","country_code":"CN","type":"facility","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366","https://openalex.org/I19820366","https://openalex.org/I4210119653","https://openalex.org/I4210124140"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Ding","raw_affiliation_strings":["CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I4210124140","https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049333864","display_name":"Tian-Yi Bao","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tian-Yi Bao","raw_affiliation_strings":["Department of Computer Science, University of Oxford, Oxford, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051929814","display_name":"He-Liang Huang","orcid":"https://orcid.org/0000-0002-5121-3028"},"institutions":[{"id":"https://openalex.org/I4210124140","display_name":"CAS Key Laboratory of Urban Pollutant Conversion","ror":"https://ror.org/02w5xy446","country_code":"CN","type":"facility","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366","https://openalex.org/I19820366","https://openalex.org/I4210119653","https://openalex.org/I4210124140"]},{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210103894","display_name":"Hefei National Center for Physical Sciences at Nanoscale","ror":"https://ror.org/01jeedh73","country_code":"CN","type":"facility","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366","https://openalex.org/I4210103894"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He-Liang Huang","raw_affiliation_strings":["CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, China","Microscale and Department of Modern Physics, Hefei National Laboratory for Physical Sciences, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I4210124140","https://openalex.org/I126520041"]},{"raw_affiliation_string":"Microscale and Department of Modern Physics, Hefei National Laboratory for Physical Sciences, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I4210103894","https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101949226"],"corresponding_institution_ids":["https://openalex.org/I126520041","https://openalex.org/I4210124140"],"apc_list":null,"apc_paid":null,"fwci":14.3919,"has_fulltext":false,"cited_by_count":151,"citation_normalized_percentile":{"value":0.99159931,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"33","issue":"12","first_page":"7210","last_page":"7222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8087109923362732},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5789473652839661},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5736026167869568},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5471526384353638},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.49985218048095703},{"id":"https://openalex.org/keywords/least-squares-support-vector-machine","display_name":"Least squares support vector machine","score":0.48630818724632263},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4785516858100891},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4773443043231964},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4524300694465637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4368003308773041},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4360957145690918},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3449339270591736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3208088278770447}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8087109923362732},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5789473652839661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5736026167869568},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5471526384353638},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.49985218048095703},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.48630818724632263},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4785516858100891},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4773443043231964},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4524300694465637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4368003308773041},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4360957145690918},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3449339270591736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3208088278770447},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3084467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3084467","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34111003","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34111003","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5977454351","display_name":null,"funder_award_id":"11905294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W199424061","https://openalex.org/W1492999010","https://openalex.org/W1596717185","https://openalex.org/W1602289806","https://openalex.org/W1979750072","https://openalex.org/W1988369744","https://openalex.org/W2073522055","https://openalex.org/W2084652510","https://openalex.org/W2103956991","https://openalex.org/W2103971661","https://openalex.org/W2117584890","https://openalex.org/W2117990954","https://openalex.org/W2120575449","https://openalex.org/W2144414190","https://openalex.org/W2153635508","https://openalex.org/W2168676717","https://openalex.org/W2499793201","https://openalex.org/W2506822747","https://openalex.org/W2559394418","https://openalex.org/W2724637409","https://openalex.org/W2752327046","https://openalex.org/W2806764558","https://openalex.org/W2880299821","https://openalex.org/W2898913178","https://openalex.org/W2899791076","https://openalex.org/W2899883790","https://openalex.org/W2945077829","https://openalex.org/W2963771752","https://openalex.org/W2964039664","https://openalex.org/W2989257188","https://openalex.org/W3101135395","https://openalex.org/W3196492698","https://openalex.org/W4252454610","https://openalex.org/W4289743945","https://openalex.org/W6608201162","https://openalex.org/W6675924963","https://openalex.org/W6677732001","https://openalex.org/W6681291431","https://openalex.org/W6703106485","https://openalex.org/W6753095413","https://openalex.org/W6755322515","https://openalex.org/W6756598837","https://openalex.org/W6770402361","https://openalex.org/W6800403941"],"related_works":["https://openalex.org/W2089892314","https://openalex.org/W1603091392","https://openalex.org/W4386075310","https://openalex.org/W2095626363","https://openalex.org/W2169565408","https://openalex.org/W2127229869","https://openalex.org/W3123056048","https://openalex.org/W2129978300","https://openalex.org/W2150638158","https://openalex.org/W2169520161"],"abstract_inverted_index":{"Support":[0],"vector":[1],"machine":[2],"(SVM)":[3],"is":[4,52,89],"a":[5,45,72,104],"particularly":[6],"powerful":[7],"and":[8,19,33,96,107,140,152],"flexible":[9],"supervised":[10],"learning":[11],"model":[12],"that":[13],"analyzes":[14],"data":[15,31,37,43,138,144,155],"for":[16,58,76,91,146],"both":[17,134],"classification":[18,125],"regression,":[20],"whose":[21],"usual":[22],"algorithm":[23,48,75,122],"complexity":[24],"scales":[25],"polynomially":[26],"with":[27,103,126],"the":[28,34,41,66,93,101,110,135,141,158,161],"dimension":[29,136],"of":[30,36,112,133,137,143,160],"space":[32,139],"number":[35,142],"points.":[38],"To":[39],"tackle":[40],"big":[42],"challenge,":[44],"quantum":[46,67,162],"SVM":[47,61,68],"was":[49],"proposed,":[50],"which":[51],"claimed":[53],"to":[54,115],"achieve":[55],"exponential":[56],"speedup":[57],"least":[59],"squares":[60],"(LS-SVM).":[62],"Here,":[63],"inspired":[64],"by":[65],"algorithm,":[69],"we":[70],"present":[71],"quantum-inspired":[73],"classical":[74],"LS-SVM.":[77],"In":[78],"our":[79,113,121],"approach,":[80],"an":[81],"improved":[82],"fast":[83],"sampling":[84,92],"technique,":[85],"namely":[86],"indirect":[87],"sampling,":[88],"proposed":[90],"kernel":[94],"matrix":[95],"classifying.":[97],"We":[98],"first":[99],"consider":[100],"LS-SVM":[102],"linear":[105],"kernel,":[106],"then":[108],"discuss":[109],"generalization":[111],"method":[114],"nonlinear":[116],"kernels.":[117],"Theoretical":[118],"analysis":[119],"shows":[120],"can":[123],"make":[124],"arbitrary":[127],"success":[128],"probability":[129],"in":[130],"logarithmic":[131],"runtime":[132,159],"points":[145],"low":[147,149],"rank,":[148],"condition":[150],"number,":[151],"high":[153],"dimensional":[154],"matrix,":[156],"matching":[157],"SVM.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":44},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
