{"id":"https://openalex.org/W4406461832","doi":"https://doi.org/10.1109/bigdata62323.2024.10825304","title":"FedPAE: Peer-Adaptive Ensemble Learning for Asynchronous and Model-Heterogeneous Federated Learning","display_name":"FedPAE: Peer-Adaptive Ensemble Learning for Asynchronous and Model-Heterogeneous Federated Learning","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461832","doi":"https://doi.org/10.1109/bigdata62323.2024.10825304"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5072696983","display_name":"Brianna Mueller","orcid":null},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Brianna Mueller","raw_affiliation_strings":["University of Iowa,Department of Business Analytics,Iowa City,USA"],"affiliations":[{"raw_affiliation_string":"University of Iowa,Department of Business Analytics,Iowa City,USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031033430","display_name":"W. Nick Street","orcid":"https://orcid.org/0000-0002-1632-5905"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. Nick Street","raw_affiliation_strings":["University of Iowa,Department of Business Analytics,Iowa City,USA"],"affiliations":[{"raw_affiliation_string":"University of Iowa,Department of Business Analytics,Iowa City,USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041162418","display_name":"Stephen Baek","orcid":"https://orcid.org/0000-0002-4758-4539"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen Baek","raw_affiliation_strings":["University of Virginia,School of Data Science,Charlottesville,USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia,School of Data Science,Charlottesville,USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090417160","display_name":"Qihang Lin","orcid":"https://orcid.org/0000-0003-2943-3267"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qihang Lin","raw_affiliation_strings":["University of Iowa,Department of Business Analytics,Iowa City,USA"],"affiliations":[{"raw_affiliation_string":"University of Iowa,Department of Business Analytics,Iowa City,USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378741","display_name":"H. J. Yang","orcid":"https://orcid.org/0009-0004-8274-9863"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingyi Yang","raw_affiliation_strings":["New York University,Department of Information Systems,New York,USA"],"affiliations":[{"raw_affiliation_string":"New York University,Department of Information Systems,New York,USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070975831","display_name":"Yankun Huang","orcid":"https://orcid.org/0009-0006-1118-6922"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yankun Huang","raw_affiliation_strings":["Arizona State University,Department of Information Systems,Tempe,USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University,Department of Information Systems,Tempe,USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5072696983"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":0.3862,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71166802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"7961","last_page":"7970"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9986000061035156,"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/T10237","display_name":"Cryptography and Data Security","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.8345614075660706},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.7936732769012451},{"id":"https://openalex.org/keywords/asynchronous-learning","display_name":"Asynchronous learning","score":0.7127606272697449},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.561958909034729},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5372974276542664},{"id":"https://openalex.org/keywords/peer-to-peer","display_name":"Peer-to-peer","score":0.5314803123474121},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.41781699657440186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35457709431648254},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2623513340950012},{"id":"https://openalex.org/keywords/synchronous-learning","display_name":"Synchronous learning","score":0.2176564633846283},{"id":"https://openalex.org/keywords/cooperative-learning","display_name":"Cooperative learning","score":0.0806785523891449},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.0606687068939209}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8345614075660706},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.7936732769012451},{"id":"https://openalex.org/C2777072894","wikidata":"https://www.wikidata.org/wiki/Q4812204","display_name":"Asynchronous learning","level":5,"score":0.7127606272697449},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.561958909034729},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5372974276542664},{"id":"https://openalex.org/C534932454","wikidata":"https://www.wikidata.org/wiki/Q161410","display_name":"Peer-to-peer","level":2,"score":0.5314803123474121},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.41781699657440186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35457709431648254},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2623513340950012},{"id":"https://openalex.org/C19122763","wikidata":"https://www.wikidata.org/wiki/Q7662215","display_name":"Synchronous learning","level":4,"score":0.2176564633846283},{"id":"https://openalex.org/C51672120","wikidata":"https://www.wikidata.org/wiki/Q303446","display_name":"Cooperative learning","level":3,"score":0.0806785523891449},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0606687068939209},{"id":"https://openalex.org/C88610354","wikidata":"https://www.wikidata.org/wiki/Q1813494","display_name":"Teaching method","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W122801842","https://openalex.org/W1562197959","https://openalex.org/W1686810756","https://openalex.org/W2100128988","https://openalex.org/W2126105956","https://openalex.org/W2127082287","https://openalex.org/W2128073546","https://openalex.org/W2135293965","https://openalex.org/W2135850590","https://openalex.org/W2164544703","https://openalex.org/W2194775991","https://openalex.org/W2273278181","https://openalex.org/W2498672755","https://openalex.org/W2604504584","https://openalex.org/W2963446712","https://openalex.org/W2972570881","https://openalex.org/W2980216952","https://openalex.org/W2990789643","https://openalex.org/W2998768810","https://openalex.org/W3012968339","https://openalex.org/W3021654819","https://openalex.org/W3039612675","https://openalex.org/W3080934299","https://openalex.org/W3099314130","https://openalex.org/W3112044954","https://openalex.org/W3120123472","https://openalex.org/W3125494587","https://openalex.org/W3129603732","https://openalex.org/W3135231128","https://openalex.org/W3183269189","https://openalex.org/W4224227775","https://openalex.org/W4246193833","https://openalex.org/W4285601288","https://openalex.org/W4285762978","https://openalex.org/W4285876308","https://openalex.org/W4287906413","https://openalex.org/W4318619660","https://openalex.org/W4382239366","https://openalex.org/W4385488466","https://openalex.org/W4386766438","https://openalex.org/W4387105517","https://openalex.org/W4387969057","https://openalex.org/W4399168337","https://openalex.org/W6604919213","https://openalex.org/W6633883679","https://openalex.org/W6637373629","https://openalex.org/W6679154154","https://openalex.org/W6679322618","https://openalex.org/W6684636516","https://openalex.org/W6728757088","https://openalex.org/W6758779121","https://openalex.org/W6759238902","https://openalex.org/W6767676916","https://openalex.org/W6768632158","https://openalex.org/W6770590064","https://openalex.org/W6772318479","https://openalex.org/W6773817997","https://openalex.org/W6774978782","https://openalex.org/W6779174293","https://openalex.org/W6779269186","https://openalex.org/W6780534440","https://openalex.org/W6784336702","https://openalex.org/W6786597537","https://openalex.org/W6787972765","https://openalex.org/W6788124332","https://openalex.org/W6789305514","https://openalex.org/W6791102956","https://openalex.org/W6791444617","https://openalex.org/W6798647746","https://openalex.org/W6849918048"],"related_works":["https://openalex.org/W4226047841","https://openalex.org/W2156559761","https://openalex.org/W3020208395","https://openalex.org/W2496167052","https://openalex.org/W1956936791","https://openalex.org/W2041343407","https://openalex.org/W4401821536","https://openalex.org/W2058515809","https://openalex.org/W4295242624","https://openalex.org/W2946278724"],"abstract_inverted_index":{"Federated":[0,107],"learning":[1,38],"(FL)":[2],"enables":[3],"multiple":[4],"clients":[5],"with":[6],"distributed":[7],"data":[8,18,31],"sources":[9],"to":[10,27,43,75,78,135],"collaboratively":[11],"train":[12],"a":[13,50,55,92,112,127,137],"shared":[14,51],"model":[15,52,119,129],"without":[16],"compromising":[17],"privacy.":[19],"However,":[20],"existing":[21,84,152],"FL":[22,70],"paradigms":[23],"face":[24],"challenges":[25],"due":[26,74],"heterogeneity":[28,120],"in":[29,62],"client":[30,81,159],"distributions":[32],"and":[33,54,64,97,121,132,143,161],"system":[34],"capabilities.":[35],"Personalized":[36],"federated":[37],"(pFL)":[39],"has":[40,71],"been":[41],"proposed":[42],"mitigate":[44],"these":[45,103],"problems,":[46],"but":[47,83],"often":[48],"requires":[49],"architecture":[53],"central":[56],"entity":[57],"for":[58],"parameter":[59],"aggregation,":[60],"resulting":[61],"scalability":[63],"communication":[65],"issues.":[66],"More":[67],"recently,":[68],"model-heterogeneous":[69],"gained":[72],"attention":[73],"its":[76],"ability":[77],"support":[79],"diverse":[80,158],"models,":[82],"methods":[85],"are":[86],"limited":[87],"by":[88],"their":[89],"dependence":[90],"on":[91],"centralized":[93],"framework,":[94],"synchronized":[95],"training,":[96],"publicly":[98],"available":[99],"datasets.":[100],"To":[101],"address":[102],"limitations,":[104],"we":[105],"introduce":[106],"Peer-Adaptive":[108],"Ensemble":[109],"Learning":[110],"(FedPAE),":[111],"fully":[113],"decentralized":[114],"pFL":[115,154],"algorithm":[116],"that":[117,149],"supports":[118],"asynchronous":[122],"learning.":[123],"Our":[124],"approach":[125],"utilizes":[126],"peer-to-peer":[128],"sharing":[130],"mechanism":[131],"ensemble":[133],"selection":[134],"achieve":[136],"more":[138],"refined":[139],"balance":[140],"between":[141],"local":[142],"global":[144],"information.":[145],"Experimental":[146],"results":[147],"show":[148],"FedPAE":[150],"outperforms":[151],"state-of-the-art":[153],"algorithms,":[155],"effectively":[156],"managing":[157],"capabilities":[160],"demonstrating":[162],"robustness":[163],"against":[164],"statistical":[165],"heterogeneity.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}