{"id":"https://openalex.org/W3092087762","doi":"https://doi.org/10.22331/q-2020-10-15-342","title":"A quantum extension of SVM-perf for training nonlinear SVMs in almost linear time","display_name":"A quantum extension of SVM-perf for training nonlinear SVMs in almost linear time","publication_year":2020,"publication_date":"2020-10-15","ids":{"openalex":"https://openalex.org/W3092087762","doi":"https://doi.org/10.22331/q-2020-10-15-342","mag":"3092087762"},"language":"en","primary_location":{"id":"doi:10.22331/q-2020-10-15-342","is_oa":true,"landing_page_url":"https://doi.org/10.22331/q-2020-10-15-342","pdf_url":"https://quantum-journal.org/papers/q-2020-10-15-342/pdf/","source":{"id":"https://openalex.org/S4210226432","display_name":"Quantum","issn_l":"2521-327X","issn":["2521-327X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317900","host_organization_name":"Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften","host_organization_lineage":["https://openalex.org/P4310317900"],"host_organization_lineage_names":["Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Quantum","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://quantum-journal.org/papers/q-2020-10-15-342/pdf/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jonathan Allcock","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jonathan Allcock","raw_affiliation_strings":["Tencent Quantum Laboratory"],"affiliations":[{"raw_affiliation_string":"Tencent Quantum Laboratory","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chang-Yu Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang-Yu Hsieh","raw_affiliation_strings":["Tencent Quantum Laboratory"],"affiliations":[{"raw_affiliation_string":"Tencent Quantum Laboratory","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":{"value":200,"currency":"EUR","value_usd":215},"apc_paid":{"value":200,"currency":"EUR","value_usd":215},"fwci":0.5485,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74161877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"4","issue":null,"first_page":"342","last_page":"342"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9340000152587891,"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":0.9340000152587891,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.034699998795986176,"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/T11804","display_name":"Quantum many-body systems","score":0.010300000198185444,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6025000214576721},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5601000189781189},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.557699978351593},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.48240000009536743},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4388999938964844},{"id":"https://openalex.org/keywords/quantum-algorithm","display_name":"Quantum algorithm","score":0.4320000112056732},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.4174000024795532},{"id":"https://openalex.org/keywords/quantum-algorithm-for-linear-systems-of-equations","display_name":"Quantum algorithm for linear systems of equations","score":0.3589000105857849},{"id":"https://openalex.org/keywords/running-time","display_name":"Running time","score":0.3327000141143799}],"concepts":[{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6025000214576721},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5601000189781189},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.557699978351593},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5533000230789185},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.529699981212616},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4388999938964844},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.4320000112056732},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36570000648498535},{"id":"https://openalex.org/C101471828","wikidata":"https://www.wikidata.org/wiki/Q17083575","display_name":"Quantum algorithm for linear systems of equations","level":5,"score":0.3589000105857849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33480000495910645},{"id":"https://openalex.org/C3017489831","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Running time","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C170122806","wikidata":"https://www.wikidata.org/wiki/Q1914828","display_name":"Linear scale","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.29100000858306885},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.26350000500679016},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C2778926657","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum system","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C192122513","wikidata":"https://www.wikidata.org/wiki/Q2835770","display_name":"Quantum phase estimation algorithm","level":5,"score":0.2547999918460846}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.22331/q-2020-10-15-342","is_oa":true,"landing_page_url":"https://doi.org/10.22331/q-2020-10-15-342","pdf_url":"https://quantum-journal.org/papers/q-2020-10-15-342/pdf/","source":{"id":"https://openalex.org/S4210226432","display_name":"Quantum","issn_l":"2521-327X","issn":["2521-327X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317900","host_organization_name":"Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften","host_organization_lineage":["https://openalex.org/P4310317900"],"host_organization_lineage_names":["Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Quantum","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2006.10299","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.10299","pdf_url":"https://arxiv.org/pdf/2006.10299","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:4869828fd9134b82862fcaa70149ccc6","is_oa":true,"landing_page_url":"https://doaj.org/article/4869828fd9134b82862fcaa70149ccc6","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Quantum, Vol 4, p 342 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.22331/q-2020-10-15-342","is_oa":true,"landing_page_url":"https://doi.org/10.22331/q-2020-10-15-342","pdf_url":"https://quantum-journal.org/papers/q-2020-10-15-342/pdf/","source":{"id":"https://openalex.org/S4210226432","display_name":"Quantum","issn_l":"2521-327X","issn":["2521-327X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317900","host_organization_name":"Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften","host_organization_lineage":["https://openalex.org/P4310317900"],"host_organization_lineage_names":["Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Quantum","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3092087762.pdf","grobid_xml":"https://content.openalex.org/works/W3092087762.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1486089539","https://openalex.org/W1512098439","https://openalex.org/W1560724230","https://openalex.org/W2035720976","https://openalex.org/W2051446825","https://openalex.org/W2065887373","https://openalex.org/W2087347434","https://openalex.org/W2103956991","https://openalex.org/W2105842272","https://openalex.org/W2107275319","https://openalex.org/W2112545207","https://openalex.org/W2119821739","https://openalex.org/W2121981260","https://openalex.org/W2137557016","https://openalex.org/W2139212933","https://openalex.org/W2139451965","https://openalex.org/W2142623206","https://openalex.org/W2144902422","https://openalex.org/W2152523366","https://openalex.org/W2153635508","https://openalex.org/W2562234976","https://openalex.org/W2792946961","https://openalex.org/W2798434869","https://openalex.org/W2880299821","https://openalex.org/W2904594696","https://openalex.org/W2930929096","https://openalex.org/W2945077829","https://openalex.org/W2964039664","https://openalex.org/W2984279929","https://openalex.org/W4250589301"],"related_works":[],"abstract_inverted_index":{"We":[0,151],"propose":[1],"a":[2,40],"quantum":[3,26,118],"algorithm":[4,33,38,155],"for":[5,12,92,106,169],"training":[6,50],"nonlinear":[7,77],"support":[8],"vector":[9],"machines":[10],"(SVM)":[11],"feature":[13],"space":[14],"learning":[15],"where":[16,95],"classical":[17,31,67],"input":[18,102],"data":[19,103,172],"is":[20,81,97],"encoded":[21],"in":[22,46,84,99,164],"the":[23,30,47,59,100,107,135,147],"amplitudes":[24],"of":[25,34,49,110,146],"states.":[27],"Based":[28],"on":[29,73],"SVM-perf":[32,68],"Joachims":[35],"\\cite{joachims2006training},":[36],"our":[37,154],"has":[39,69],"running":[41],"time":[42],"which":[43,141],"scales":[44],"linearly":[45],"number":[48],"examples<mml:math":[51],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>m</mml:mi></mml:math>(up":[52],"to":[53,58,129],"polylogarithmic":[54],"factors)":[55],"and":[56,76,156,166],"applies":[57],"standard":[60],"soft-margin<mml:math":[61,148],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msub><mml:mi>\u2113</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:math>-SVM":[62,149],"model.":[63,150],"In":[64],"contrast,":[65],"while":[66],"demonstrated":[70],"impressive":[71],"performance":[72],"both":[74],"linear":[75,93],"SVMs,":[78,94],"its":[79],"efficiency":[80],"guaranteed":[82],"only":[83,91,168],"certain":[85,143],"cases:":[86],"it":[87,160],"achieves":[88],"linear<mml:math":[89],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>m</mml:mi></mml:math>scaling":[90],"classification":[96],"performed":[98],"original":[101],"space,":[104],"or":[105,112,126,137],"special":[108],"cases":[109],"low-rank":[111],"shift-invariant":[113],"kernels.":[114],"Similarly,":[115],"previously":[116],"proposed":[117],"algorithms":[119],"either":[120],"have":[121],"super-linear":[122],"scaling":[123],"in<mml:math":[124],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>m</mml:mi></mml:math>,":[125],"else":[127],"apply":[128],"different":[130],"SVM":[131],"models":[132],"such":[133],"as":[134],"hard-margin":[136],"least":[138],"squares<mml:math":[139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msub><mml:mi>\u2113</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math>-SVM":[140],"lack":[142],"desirable":[144],"properties":[145],"classically":[152],"simulate":[153],"give":[157],"evidence":[158],"that":[159],"can":[161],"perform":[162],"well":[163],"practice,":[165],"not":[167],"asymptotically":[170],"large":[171],"sets.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2020-10-15T00:00:00"}
