{"id":"https://openalex.org/W3137547140","doi":"https://doi.org/10.1007/s13042-021-01281-0","title":"Universal consistency of twin support vector machines","display_name":"Universal consistency of twin support vector machines","publication_year":2021,"publication_date":"2021-03-14","ids":{"openalex":"https://openalex.org/W3137547140","doi":"https://doi.org/10.1007/s13042-021-01281-0","mag":"3137547140"},"language":"en","primary_location":{"id":"doi:10.1007/s13042-021-01281-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-021-01281-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-021-01281-0.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s13042-021-01281-0.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100623943","display_name":"Weixia Xu","orcid":"https://orcid.org/0009-0007-6327-7372"},"institutions":[{"id":"https://openalex.org/I146613903","display_name":"Shanghai Lixin University of Accounting and Finance","ror":"https://ror.org/02g81yf77","country_code":"CN","type":"education","lineage":["https://openalex.org/I146613903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixia Xu","raw_affiliation_strings":["School of Information Management, Shanghai Lixin University of Accounting and Finance, Shanghai, 201209, China"],"affiliations":[{"raw_affiliation_string":"School of Information Management, Shanghai Lixin University of Accounting and Finance, Shanghai, 201209, China","institution_ids":["https://openalex.org/I146613903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101940253","display_name":"Dingjiang Huang","orcid":"https://orcid.org/0000-0002-0144-7344"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingjiang Huang","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, 200062, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, 200062, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017862559","display_name":"Shuigeng Zhou","orcid":"https://orcid.org/0000-0002-1949-2768"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuigeng Zhou","raw_affiliation_strings":["School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, 200433, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, 200433, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5017862559"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":{"value":2790,"currency":"EUR","value_usd":3590},"apc_paid":{"value":2790,"currency":"EUR","value_usd":3590},"fwci":0.1397,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52254094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"12","issue":"7","first_page":"1867","last_page":"1877"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9836000204086304,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7641454339027405},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6813421249389648},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5548603534698486},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5408767461776733},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.494478702545166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48481741547584534},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4546736180782318},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.452056348323822},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44640517234802246},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4416927695274353},{"id":"https://openalex.org/keywords/bayes-classifier","display_name":"Bayes classifier","score":0.43849989771842957},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43169930577278137},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35871079564094543}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7641454339027405},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6813421249389648},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5548603534698486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5408767461776733},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.494478702545166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48481741547584534},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4546736180782318},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.452056348323822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44640517234802246},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4416927695274353},{"id":"https://openalex.org/C185207860","wikidata":"https://www.wikidata.org/wiki/Q17004744","display_name":"Bayes classifier","level":4,"score":0.43849989771842957},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43169930577278137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35871079564094543},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s13042-021-01281-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-021-01281-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-021-01281-0.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s13042-021-01281-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-021-01281-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-021-01281-0.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1487418658","display_name":null,"funder_award_id":"61972100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4839713446","display_name":null,"funder_award_id":"6197210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G783048903","display_name":null,"funder_award_id":"No. 61972100","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3137547140.pdf","grobid_xml":"https://content.openalex.org/works/W3137547140.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W31995902","https://openalex.org/W326055820","https://openalex.org/W1564947197","https://openalex.org/W1850992575","https://openalex.org/W1968436459","https://openalex.org/W1986190044","https://openalex.org/W1990064648","https://openalex.org/W2012556673","https://openalex.org/W2014908235","https://openalex.org/W2029538739","https://openalex.org/W2057192935","https://openalex.org/W2081130435","https://openalex.org/W2084840427","https://openalex.org/W2090089568","https://openalex.org/W2109445534","https://openalex.org/W2110630246","https://openalex.org/W2119851445","https://openalex.org/W2132425109","https://openalex.org/W2140509289","https://openalex.org/W2155195660","https://openalex.org/W2170860445","https://openalex.org/W2398429633","https://openalex.org/W2492794003","https://openalex.org/W2599929987","https://openalex.org/W2757101026","https://openalex.org/W2780921808","https://openalex.org/W2804758133","https://openalex.org/W2805746648","https://openalex.org/W2952550171","https://openalex.org/W2990138404","https://openalex.org/W3091238722","https://openalex.org/W3104183394","https://openalex.org/W3104898220","https://openalex.org/W4238284510","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2374047926","https://openalex.org/W2394466068","https://openalex.org/W2381401419","https://openalex.org/W2383501440","https://openalex.org/W4312866165","https://openalex.org/W145653800","https://openalex.org/W2957157835","https://openalex.org/W83434975","https://openalex.org/W2393473353","https://openalex.org/W2606238806"],"abstract_inverted_index":{"Abstract":[0],"A":[1,48],"classification":[2,25,46,89,108,144,165],"problem":[3,26],"aims":[4],"at":[5],"constructing":[6],"a":[7,24,38,142,149],"best":[8],"classifier":[9],"with":[10],"the":[11,15,20,43,54,56,60,63,66,69,83,136,159,173],"smallest":[12],"risk.":[13],"When":[14],"sample":[16,57],"size":[17,58],"approaches":[18],"infinity,":[19],"learning":[21],"algorithms":[22],"for":[23,120,152,163,193,203],"are":[27,78,229],"characterized":[28],"by":[29],"an":[30],"asymptotical":[31],"property,":[32],"i.e.,":[33],"universal":[34,49,137,174,191,199],"consistency.":[35],"It":[36],"plays":[37],"crucial":[39],"role":[40],"in":[41,87,113,127,130,141],"measuring":[42],"construction":[44],"of":[45,59,68,82,107,139,158,161,176,186,221,227],"rules.":[47],"consistent":[50],"algorithm":[51,61],"ensures":[52],"that":[53,155,198],"larger":[55],"is,":[62],"more":[64],"accurately":[65],"distribution":[67],"samples":[70],"could":[71],"be":[72],"reconstructed.":[73],"Support":[74],"vector":[75,99],"machines":[76,100],"(SVMs)":[77],"regarded":[79],"as":[80,103],"one":[81],"most":[84,157],"important":[85],"models":[86],"binary":[88,143,164],"problems.":[90,166],"How":[91],"to":[92,96,104],"effectively":[93],"extend":[94],"SVMs":[95],"twin":[97],"support":[98],"(TWSVMs)":[101],"so":[102],"improve":[105],"performance":[106],"has":[109],"gained":[110],"increasing":[111],"interest":[112],"many":[114],"research":[115],"areas":[116],"recently.":[117],"Many":[118],"variants":[119,160,226],"TWSVMs":[121,140,162,228],"have":[122],"been":[123],"proposed":[124],"and":[125,190,217],"used":[126],"practice.":[128],"Thus":[129],"this":[131],"paper,":[132],"we":[133,170,181],"focus":[134],"on":[135,168],"consistency":[138,175,192,200],"setting.":[145],"We":[146],"first":[147],"give":[148,182],"general":[150,223],"framework":[151],"TWSVM":[153,205],"classifiers":[154,206],"unifies":[156],"Based":[167],"it,":[169],"then":[171],"investigate":[172],"TWSVMs.":[177,194],"To":[178],"do":[179],"this,":[180],"some":[183,208],"useful":[184],"definitions":[185],"risk,":[187],"Bayes":[188],"risk":[189],"Theoretical":[195],"results":[196],"indicate":[197],"is":[201],"valid":[202],"various":[204],"under":[207],"certain":[209],"conditions,":[210],"including":[211],"covering":[212,215],"number,":[213],"localized":[214],"number":[216],"stability.":[218],"For":[219],"applications":[220],"our":[222],"framework,":[224],"several":[225],"considered.":[230]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
