{"id":"https://openalex.org/W4415707716","doi":"https://doi.org/10.1109/icme59968.2025.11209954","title":"Long-Tailed Federated Learning with Fixed Classifier","display_name":"Long-Tailed Federated Learning with Fixed Classifier","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415707716","doi":"https://doi.org/10.1109/icme59968.2025.11209954"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5100421343","display_name":"Yi Li","orcid":"https://orcid.org/0000-0001-8425-7871"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Li","raw_affiliation_strings":["Dalian University of Technology,School of Future Technology/School of Artificial Inteligence,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Future Technology/School of Artificial Inteligence,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637375","display_name":"Weichao Li","orcid":"https://orcid.org/0000-0001-5567-2283"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weichao Li","raw_affiliation_strings":["Dalian University of Technology,School of Information and Communication Engineering,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Information and Communication Engineering,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008089079","display_name":"Xin Zheng","orcid":"https://orcid.org/0000-0001-5285-4989"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xin Zheng","raw_affiliation_strings":["Griffith University,School of Information and Communication Technology,Gold Coast,Australia"],"affiliations":[{"raw_affiliation_string":"Griffith University,School of Information and Communication Technology,Gold Coast,Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071538073","display_name":"Haiyan Fu","orcid":"https://orcid.org/0000-0002-0865-0652"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Fu","raw_affiliation_strings":["Dalian University of Technology,School of Information and Communication Engineering,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Information and Communication Engineering,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056699273","display_name":"Yanqing Guo","orcid":"https://orcid.org/0000-0001-9123-140X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqing Guo","raw_affiliation_strings":["Dalian University of Technology,School of Future Technology/School of Artificial Inteligence,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Future Technology/School of Artificial Inteligence,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100421343"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17500218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8098999857902527,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8098999857902527,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.05649999901652336,"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/T11719","display_name":"Data Quality and Management","score":0.016599999740719795,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.633899986743927},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6061000227928162},{"id":"https://openalex.org/keywords/standardization","display_name":"Standardization","score":0.4505999982357025},{"id":"https://openalex.org/keywords/sample-space","display_name":"Sample space","score":0.4277999997138977},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4092000126838684},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.40799999237060547},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3799999952316284},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.36959999799728394},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.36410000920295715},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.36230000853538513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239000201225281},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.633899986743927},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6061000227928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5684999823570251},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.487199991941452},{"id":"https://openalex.org/C188087704","wikidata":"https://www.wikidata.org/wiki/Q369577","display_name":"Standardization","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43720000982284546},{"id":"https://openalex.org/C100279318","wikidata":"https://www.wikidata.org/wiki/Q467440","display_name":"Sample space","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.40799999237060547},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.32600000500679016},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C3019722297","wikidata":"https://www.wikidata.org/wiki/Q4440864","display_name":"High dimensional","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2086869478","https://openalex.org/W2962895364","https://openalex.org/W2963691377","https://openalex.org/W3065974826","https://openalex.org/W3159623990","https://openalex.org/W3171998492","https://openalex.org/W3176639943","https://openalex.org/W4229029907","https://openalex.org/W4285174182","https://openalex.org/W4285603347","https://openalex.org/W4285815152","https://openalex.org/W4366352743","https://openalex.org/W4387717607","https://openalex.org/W4390873683","https://openalex.org/W4393160079"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1,6],"(FL)":[2],"is":[3],"a":[4,12,63,81,133,138],"machine":[5],"approach":[7],"where":[8],"multiple":[9],"participants":[10],"train":[11],"model":[13],"together":[14],"without":[15],"sharing":[16],"their":[17],"privacy":[18],"data.":[19],"The":[20,96],"challenge":[21],"of":[22,110,115,119],"long-tail":[23,46,92,154],"data":[24,30,38],"heterogeneity":[25],"in":[26,37,48,50,94,150],"FL":[27,151],"causes":[28],"imbalanced":[29],"distribution":[31,47,93],"among":[32],"clients":[33],"and":[34,80,102],"significant":[35],"disparities":[36],"quantities":[39],"across":[40,121],"different":[41,122],"classes.":[42],"To":[43],"tackle":[44],"the":[45,57,68,91,107,113,116,125],"FL,":[49],"this":[51],"paper,":[52],"we":[53,130],"draw":[54],"inspiration":[55],"from":[56],"equiangular":[58],"tight":[59],"frame":[60],"to":[61,89,105],"establish":[62],"fixed":[64,85],"balanced":[65],"classifier,":[66],"enhancing":[67],"model\u2019s":[69],"generalization":[70],"ability":[71],"for":[72],"classes":[73,123],"with":[74,84,153],"fewer":[75],"instances.":[76],"Therefore,":[77],"feature":[78,108],"extractors":[79],"loss":[82,136],"aligned":[83],"classifiers":[86],"are":[87],"designed":[88],"address":[90],"FL.":[95],"algorithm":[97,146],"also":[98,131],"utilizes":[99],"Sample":[100],"Standardization":[101],"Batch":[103],"Normalization":[104],"standardize":[106],"space":[109],"samples,":[111],"preventing":[112],"impact":[114],"magnitude":[117],"difference":[118],"features":[120],"on":[124],"prediction":[126],"probability.":[127],"In":[128],"addition,":[129],"propose":[132],"logit":[134],"adjustment":[135],"under":[137],"mixed":[139],"low-temperature":[140],"setting.":[141],"Experiments":[142],"demonstrate":[143],"that":[144],"our":[145],"outperforms":[147],"state-of-the-art":[148],"methods":[149],"settings":[152],"distribution.":[155]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}