{"id":"https://openalex.org/W4388837948","doi":"https://doi.org/10.1109/tfuzz.2023.3333571","title":"A Novel Fuzzy Large Margin Distribution Machine With Unified Pinball Loss","display_name":"A Novel Fuzzy Large Margin Distribution Machine With Unified Pinball Loss","publication_year":2023,"publication_date":"2023-11-20","ids":{"openalex":"https://openalex.org/W4388837948","doi":"https://doi.org/10.1109/tfuzz.2023.3333571"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2023.3333571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2023.3333571","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5053928029","display_name":"Libo Zhang","orcid":"https://orcid.org/0000-0001-5992-0790"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Libo Zhang","raw_affiliation_strings":["School of Aritificial Intelligence, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Aritificial Intelligence, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041425113","display_name":"Denghao Dong","orcid":"https://orcid.org/0000-0001-6585-0928"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Denghao Dong","raw_affiliation_strings":["School of Aritificial Intelligence, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Aritificial Intelligence, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100579628","display_name":"Lianyi Luo","orcid":"https://orcid.org/0009-0008-1844-0043"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianyi Luo","raw_affiliation_strings":["School of Aritificial Intelligence, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Aritificial Intelligence, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100616362","display_name":"Dun Liu","orcid":"https://orcid.org/0000-0002-1768-4598"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dun Liu","raw_affiliation_strings":["School of Economics and Management, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053928029"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":0.4939,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66417901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"32","issue":"4","first_page":"1782","last_page":"1795"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980000257492065,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9937000274658203,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9936000108718872,"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/hinge-loss","display_name":"Hinge loss","score":0.7390044927597046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.650007426738739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5609850883483887},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48209598660469055},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4573400318622589},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45695000886917114},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.44439876079559326},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.41298994421958923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3871539235115051}],"concepts":[{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.7390044927597046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.650007426738739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5609850883483887},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48209598660469055},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4573400318622589},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45695000886917114},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.44439876079559326},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.41298994421958923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3871539235115051},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2023.3333571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2023.3333571","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G3413195688","display_name":null,"funder_award_id":"62106205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5186812915","display_name":null,"funder_award_id":"62276217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6203267807","display_name":null,"funder_award_id":"2022JDJQ0034","funder_id":"https://openalex.org/F4320336820","funder_display_name":"Science Fund for Distinguished Young Scholars of Sichuan Province"},{"id":"https://openalex.org/G8063529500","display_name":null,"funder_award_id":"cstc2021jcyj-msxmX0824","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336820","display_name":"Science Fund for Distinguished Young Scholars of Sichuan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1969535228","https://openalex.org/W1995450389","https://openalex.org/W2015913315","https://openalex.org/W2017776670","https://openalex.org/W2074651608","https://openalex.org/W2115242586","https://openalex.org/W2129763352","https://openalex.org/W2136627475","https://openalex.org/W2151509918","https://openalex.org/W2154179941","https://openalex.org/W2156145910","https://openalex.org/W2156909104","https://openalex.org/W2170860445","https://openalex.org/W2187089797","https://openalex.org/W2292553612","https://openalex.org/W2312471699","https://openalex.org/W2343106965","https://openalex.org/W2460759951","https://openalex.org/W2534830764","https://openalex.org/W2594577230","https://openalex.org/W2753871781","https://openalex.org/W2785828297","https://openalex.org/W2788883687","https://openalex.org/W2910487174","https://openalex.org/W2912088361","https://openalex.org/W2955345977","https://openalex.org/W2997546679","https://openalex.org/W3015988562","https://openalex.org/W3020067472","https://openalex.org/W3081161286","https://openalex.org/W3093031590","https://openalex.org/W3093703605","https://openalex.org/W3136529629","https://openalex.org/W3183935632","https://openalex.org/W3201854766","https://openalex.org/W4210388988","https://openalex.org/W4220693559","https://openalex.org/W4230846333","https://openalex.org/W4285308876","https://openalex.org/W4320008838","https://openalex.org/W4321609006","https://openalex.org/W6682742115"],"related_works":["https://openalex.org/W2036329542","https://openalex.org/W2942806827","https://openalex.org/W2163046677","https://openalex.org/W4382322253","https://openalex.org/W2941035935","https://openalex.org/W4288375424","https://openalex.org/W4289674694","https://openalex.org/W2136627475","https://openalex.org/W2159903183","https://openalex.org/W2741102186"],"abstract_inverted_index":{"On":[0],"the":[1,4,15,20,25,48,68,73,89,134,145,156,159,173,178,201,205,208,229,265],"basis":[2],"of":[3,63,127,147,204,231,249,269],"support":[5],"vector":[6],"machine":[7],"(SVM),":[8],"Large":[9,102],"Margin":[10,103],"Distribution":[11,104],"Machine":[12,105],"(LDM)":[13],"improves":[14],"generalization":[16],"performance":[17],"by":[18,81,195],"incorporating":[19],"marginal":[21],"distribution":[22],"theory.":[23],"Nevertheless,":[24],"current":[26],"LDM":[27],"models":[28],"(LDMs)":[29],"still":[30],"exhibit":[31],"limitations":[32],"when":[33],"it":[34,148],"comes":[35],"to":[36,45,78,141,162],"handling":[37],"noisy":[38],"data,":[39],"such":[40],"as:":[41,114],"i)":[42,115],"LDMs":[43,64],"fails":[44],"effectively":[46],"discern":[47],"samples":[49],"being":[50,149],"noise":[51,167,196,202,214,219,234],"and":[52,93,97,130,165,197,217,240,259,267],"consequently":[53],"falls":[54],"short":[55],"in":[56],"robust":[57],"defenses.":[58],"ii)":[59,171],"The":[60,136,182],"hinge":[61,174],"loss":[62,95,175,184],"is":[65,112,121,186,192],"predicated":[66],"upon":[67],"minimal":[69],"inter-category":[70],"separation,":[71],"rendering":[72],"corresponding":[74],"classifier":[75,206],"highly":[76],"susceptible":[77],"perturbations":[79],"induced":[80],"noise.":[82,152],"To":[83],"address":[84],"these":[85],"limitations,":[86],"we":[87,245],"leverage":[88],"fuzzy":[90,118],"set":[91],"theory":[92],"pinball":[94,180,183],"function,":[96],"propose":[98],"a":[99,139,154,247],"novel":[100],"Fuzzy":[101],"with":[106,133,177],"Unified":[107],"Pinball":[108],"Loss":[109],"(FUPLDM),":[110],"which":[111,191,263],"performed":[113],"An":[116],"innovative":[117],"membership":[119],"function":[120,137,176,185],"developed,":[122],"utilizing":[123],"two":[124],"distinct":[125],"types":[126],"feature":[128],"centers":[129],"their":[131],"associations":[132],"samples.":[135],"assigns":[138],"probability":[140],"each":[142],"sample,":[143],"indicating":[144],"likelihood":[146],"classified":[150],"as":[151],"As":[153],"result,":[155],"model":[157],"gains":[158],"remarkable":[160],"ability":[161],"accurately":[163],"identify":[164],"distinguish":[166],"from":[168],"other":[169],"data.":[170],"Replace":[172],"unified":[179],"loss.":[181],"based":[187],"on":[188,252],"interquartile":[189],"distance,":[190,237],"less":[193],"affected":[194],"can":[198],"well":[199],"improve":[200],"immunity":[203],"at":[207],"boundary.":[209],"Therefore,":[210],"FUPLDM":[211],"has":[212],"superior":[213],"recognition":[215],"capabilities":[216],"substantial":[218],"resistance":[220],"against":[221],"its":[222],"detrimental":[223],"effects.":[224],"Furthermore,":[225],"We":[226],"also":[227],"analyzed":[228],"properties":[230],"FUPLDM,":[232],"including":[233],"insensitivity,":[235],"intra-class":[236],"inter-class":[238],"scatter,":[239],"misclassification":[241],"error.":[242],"At":[243],"last,":[244],"conduct":[246],"series":[248],"comparative":[250],"experiments":[251],"artificial":[253],"synthetic":[254],"datasets,":[255,258,262],"UCI":[256,261],"benchmark":[257],"noise-added":[260],"demonstrate":[264],"effectiveness":[266],"superiority":[268],"FUPLDM.":[270]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
