{"id":"https://openalex.org/W4401857167","doi":"https://doi.org/10.1145/3637528.3671748","title":"FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning","display_name":"FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401857167","doi":"https://doi.org/10.1145/3637528.3671748"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671748","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5057905164","display_name":"Zihui Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihui Wang","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0009-0006-9923-8968","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zheng Wang","orcid":"https://orcid.org/0009-0003-3705-7393"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0009-0003-3705-7393","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052577882","display_name":"Lingjuan Lyu","orcid":"https://orcid.org/0000-0003-3170-4994"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lingjuan Lyu","raw_affiliation_strings":["Sony AI, Zurich, Swaziland"],"raw_orcid":"https://orcid.org/0000-0003-3170-4994","affiliations":[{"raw_affiliation_string":"Sony AI, Zurich, Swaziland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101576672","display_name":"Zhaopeng Peng","orcid":"https://orcid.org/0009-0006-6122-1108"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaopeng Peng","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0009-0006-6122-1108","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106708584","display_name":"Zhicheng Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhicheng Yang","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0009-0000-1316-7000","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047386824","display_name":"Chenglu Wen","orcid":"https://orcid.org/0000-0002-6189-1236"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglu Wen","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-6189-1236","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068270780","display_name":"Rongshan Yu","orcid":"https://orcid.org/0000-0003-2179-173X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rongshan Yu","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, National University of Singapore, Xiamen, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-2179-173X","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, National University of Singapore, Xiamen, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416961","display_name":"Cheng Wang","orcid":"https://orcid.org/0000-0001-6075-796X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0001-6075-796X","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047023776","display_name":"Xiaoliang Fan","orcid":"https://orcid.org/0000-0002-6958-6658"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoliang Fan","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-6958-6658","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3299","last_page":"3310"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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":0.9994000196456909,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.968500018119812,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11045","display_name":"Privacy, Security, and Data Protection","score":0.9467999935150146,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8327898979187012},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.8251245617866516},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6989226341247559},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4602031409740448},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4487322270870209},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4240206480026245},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4221356511116028},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4141848087310791},{"id":"https://openalex.org/keywords/collaborative-learning","display_name":"Collaborative learning","score":0.4134840965270996},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.33351361751556396},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.2691919803619385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18003177642822266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8327898979187012},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.8251245617866516},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6989226341247559},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4602031409740448},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4487322270870209},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4240206480026245},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4221356511116028},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4141848087310791},{"id":"https://openalex.org/C138020889","wikidata":"https://www.wikidata.org/wiki/Q2349659","display_name":"Collaborative learning","level":2,"score":0.4134840965270996},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33351361751556396},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2691919803619385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18003177642822266},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671748","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":32,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2594481151","https://openalex.org/W2900182564","https://openalex.org/W2914937732","https://openalex.org/W2962696932","https://openalex.org/W2963145730","https://openalex.org/W2965862774","https://openalex.org/W2995191368","https://openalex.org/W3005429940","https://openalex.org/W3035453001","https://openalex.org/W3104924399","https://openalex.org/W3108051446","https://openalex.org/W3109051775","https://openalex.org/W3110176593","https://openalex.org/W3134509799","https://openalex.org/W3135472452","https://openalex.org/W3156681210","https://openalex.org/W3212504668","https://openalex.org/W3214721897","https://openalex.org/W4283793425","https://openalex.org/W4285483502","https://openalex.org/W4287322665","https://openalex.org/W4301409532","https://openalex.org/W4311630441","https://openalex.org/W4312699393","https://openalex.org/W4312869277","https://openalex.org/W4320719463","https://openalex.org/W4364302664","https://openalex.org/W4382318655","https://openalex.org/W4385568263","https://openalex.org/W4386066601","https://openalex.org/W4386071645"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2363545964"],"abstract_inverted_index":{"Collaborative":[0,86],"fairness":[1,63,102,106,196],"stands":[2],"as":[3,43,204],"an":[4],"essential":[5],"element":[6],"in":[7,67,194,213],"federated":[8,214],"learning":[9,79],"to":[10,32,51,110,118,163],"encourage":[11],"client":[12,211],"participation":[13,212],"by":[14,89,107],"equitably":[15],"distributing":[16],"rewards":[17,109],"based":[18,113],"on":[19,26,114,183],"individual":[20,111],"contributions.":[21,116],"Existing":[22],"methods":[23,193],"primarily":[24],"focus":[25],"adjusting":[27],"gradient":[28],"allocations":[29],"among":[30],"clients":[31,112,138],"achieve":[33],"collaborative":[34,101],"fairness.":[35,133],"However,":[36],"they":[37],"frequently":[38],"overlook":[39],"crucial":[40,147],"factors":[41],"such":[42],"maintaining":[44],"consistency":[45,151],"across":[46,152],"local":[47,153],"models":[48],"and":[49,64,174,197],"catering":[50],"the":[52,97,120,168],"diverse":[53,144],"requirements":[54],"of":[55,99,132,146,171],"high-contributing":[56,137],"clients.":[57],"This":[58,134],"oversight":[59],"inevitably":[60],"decreases":[61],"both":[62,195],"model":[65,178,198],"accuracy":[66],"practice.":[68],"To":[69],"address":[70],"these":[71],"issues,":[72],"we":[73,95,122,156],"propose":[74],"FedSAC,":[75],"a":[76,90,124,129,143,159,205],"novel":[77],"Federated":[78],"framework":[80],"with":[81,128,139],"dynamic":[82,160],"Submodel":[83],"Allocation":[84],"for":[85],"fairness,":[87],"backed":[88],"theoretical":[91,130],"convergence":[92],"guarantee.":[93],"First,":[94],"present":[96],"concept":[98],"\"bounded":[100],"(BCF)\",":[103],"which":[104],"ensures":[105],"tailoring":[108],"their":[115],"Second,":[117],"implement":[119],"BCF,":[121],"design":[123],"submodel":[125],"allocation":[126],"module":[127,135,162],"guarantee":[131],"incentivizes":[136],"high-performance":[140],"submodels":[141],"containing":[142],"range":[145],"neurons,":[148],"thereby":[149],"preserving":[150],"models.":[154],"Third,":[155],"further":[157],"develop":[158],"aggregation":[161],"adaptively":[164],"aggregate":[165],"submodels,":[166],"ensuring":[167],"equitable":[169],"treatment":[170],"low-frequency":[172],"neurons":[173],"consequently":[175],"enhancing":[176],"overall":[177],"accuracy.":[179,199],"Extensive":[180],"experiments":[181],"conducted":[182],"three":[184],"public":[185],"benchmarks":[186],"demonstrate":[187],"that":[188],"FedSAC":[189],"outperforms":[190],"all":[191],"baseline":[192],"We":[200],"see":[201],"this":[202],"work":[203],"significant":[206],"step":[207],"towards":[208],"incentivizing":[209],"broader":[210],"learning.":[215],"The":[216],"source":[217],"code":[218],"is":[219],"available":[220],"at":[221],"https://github.com/wangzihuixmu/FedSAC.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
