{"id":"https://openalex.org/W4309794509","doi":"https://doi.org/10.1109/tbdata.2022.3222971","title":"Towards Effective Clustered Federated Learning: A Peer-to-Peer Framework With Adaptive Neighbor Matching","display_name":"Towards Effective Clustered Federated Learning: A Peer-to-Peer Framework With Adaptive Neighbor Matching","publication_year":2022,"publication_date":"2022-11-17","ids":{"openalex":"https://openalex.org/W4309794509","doi":"https://doi.org/10.1109/tbdata.2022.3222971"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2022.3222971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2022.3222971","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","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/A5031648019","display_name":"Zexi Li","orcid":null},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zexi Li","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073424019","display_name":"Jiaxun Lu","orcid":"https://orcid.org/0000-0001-6527-4430"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxun Lu","raw_affiliation_strings":["Huawei Noah&#x0027;s Ark Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x0027;s Ark Lab, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741069","display_name":"Shuang Luo","orcid":"https://orcid.org/0000-0003-2621-9193"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Luo","raw_affiliation_strings":["School of Public Affairs, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Public Affairs, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038022012","display_name":"Didi Zhu","orcid":"https://orcid.org/0009-0004-6892-5357"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Didi Zhu","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015563699","display_name":"Yunfeng Shao","orcid":"https://orcid.org/0000-0002-4335-5157"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfeng Shao","raw_affiliation_strings":["Huawei Noah&#x0027;s Ark Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x0027;s Ark Lab, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002949162","display_name":"Yinchuan Li","orcid":"https://orcid.org/0000-0002-4263-5130"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinchuan Li","raw_affiliation_strings":["Huawei Noah&#x0027;s Ark Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x0027;s Ark Lab, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101409714","display_name":"Zhimeng Zhang","orcid":"https://orcid.org/0000-0002-3695-1129"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhimeng Zhang","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057416382","display_name":"Yongheng Wang","orcid":"https://orcid.org/0000-0002-7675-2327"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongheng Wang","raw_affiliation_strings":["Big Data Intelligence Research Center, Zhejiang Lab, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Big Data Intelligence Research Center, Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056838798","display_name":"Chao Wu","orcid":"https://orcid.org/0000-0003-0885-6869"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wu","raw_affiliation_strings":["School of Public Affairs, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Public Affairs, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5031648019"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":null,"apc_paid":null,"fwci":5.6551,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.96485158,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"10","issue":"6","first_page":"812","last_page":"826"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.994700014591217,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9381999969482422,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8482780456542969},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.602056086063385},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5512068867683411},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4747866988182068},{"id":"https://openalex.org/keywords/peer-to-peer","display_name":"Peer-to-peer","score":0.4303937554359436},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.42676225304603577},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41195639967918396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34590816497802734},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32087138295173645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29834601283073425},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.22949662804603577}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8482780456542969},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.602056086063385},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5512068867683411},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4747866988182068},{"id":"https://openalex.org/C534932454","wikidata":"https://www.wikidata.org/wiki/Q161410","display_name":"Peer-to-peer","level":2,"score":0.4303937554359436},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.42676225304603577},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41195639967918396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34590816497802734},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32087138295173645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29834601283073425},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.22949662804603577},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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/tbdata.2022.3222971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2022.3222971","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G8451288410","display_name":null,"funder_award_id":"U19B2042","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1565327149","https://openalex.org/W2100659887","https://openalex.org/W2112796928","https://openalex.org/W2140910558","https://openalex.org/W2335728318","https://openalex.org/W2596636257","https://openalex.org/W2750384547","https://openalex.org/W2912213068","https://openalex.org/W2913243576","https://openalex.org/W2998705539","https://openalex.org/W3021654819","https://openalex.org/W3025098563","https://openalex.org/W3080934299","https://openalex.org/W3091635927","https://openalex.org/W3093423391","https://openalex.org/W3097817814","https://openalex.org/W3116402990","https://openalex.org/W3118608800","https://openalex.org/W3130294722","https://openalex.org/W3153537487","https://openalex.org/W3155912831","https://openalex.org/W3159080474","https://openalex.org/W3161501971","https://openalex.org/W3164573547","https://openalex.org/W3171826865","https://openalex.org/W3172811949","https://openalex.org/W3182125009","https://openalex.org/W3183269189","https://openalex.org/W3193589553","https://openalex.org/W3196371845","https://openalex.org/W3209948389","https://openalex.org/W4200635003","https://openalex.org/W4206320562","https://openalex.org/W4280551141","https://openalex.org/W4287788058","https://openalex.org/W6633949838","https://openalex.org/W6639480849","https://openalex.org/W6703116779","https://openalex.org/W6728757088","https://openalex.org/W6738250615","https://openalex.org/W6743688258","https://openalex.org/W6748544923","https://openalex.org/W6758455886","https://openalex.org/W6770046221","https://openalex.org/W6779269186","https://openalex.org/W6784298528","https://openalex.org/W6784327799","https://openalex.org/W6786597537","https://openalex.org/W6787972765","https://openalex.org/W6789592126","https://openalex.org/W6790114788","https://openalex.org/W6793650020","https://openalex.org/W6798647746","https://openalex.org/W6802618294","https://openalex.org/W6841242722"],"related_works":["https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W1975321310","https://openalex.org/W2990323019","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2095350775","https://openalex.org/W1972035260","https://openalex.org/W2375480909","https://openalex.org/W2014842417"],"abstract_inverted_index":{"In":[0,41,69,90],"federated":[1],"learning":[2],"(FL),":[3],"clients":[4,33,95],"may":[5],"have":[6,136,159],"diverse":[7],"objectives,":[8],"and":[9,36,56,116,126,150,167,173,188],"merging":[10],"all":[11],"clients'":[12],"knowledge":[13],"into":[14,34],"one":[15],"global":[16,39],"model":[17],"will":[18],"cause":[19],"negative":[20],"transfer":[21],"to":[22,30,62,99,154,183],"local":[23],"performance.":[24],"Thus,":[25],"clustered":[26,45,104,156,169],"FL":[27,46,83,186,197],"is":[28,181,202],"proposed":[29,179],"group":[31],"similar":[32],"clusters":[35,55],"maintain":[37],"several":[38],"models.":[40],"the":[42,49,52,64,74,130,145,151,155,178,184,194],"literature,":[43],"centralized":[44,195],"algorithms":[47],"require":[48],"assumption":[50],"of":[51,54,76,140,147],"number":[53,75],"hence":[57],"are":[58],"not":[59],"effective":[60,103,203],"enough":[61],"explore":[63],"latent":[65],"relationships":[66],"among":[67],"clients.":[68],"this":[70],"paper,":[71],"without":[72],"assuming":[73],"clusters,":[77],"we":[78,107],"propose":[79],"a":[80,117],"peer-to-peer":[81],"(P2P)":[82],"algorithm":[84,121,180],"named":[85],"<monospace":[86,91,141,199],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[87,92,142,200],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">PANM</monospace>":[88,93,143,201],".":[89],",":[94],"communicate":[96],"with":[97],"peers":[98],"adaptively":[100],"form":[101],"an":[102],"topology.":[105],"Specifically,":[106],"present":[108],"two":[109],"novel":[110],"metrics":[111],"for":[112],"measuring":[113],"client":[114],"similarity":[115],"two-stage":[118],"neighbor":[119,148],"matching":[120],"based":[122],"Monte":[123],"Carlo":[124],"method":[125],"Expectation":[127],"Maximization":[128],"under":[129,164,205],"Gaussian":[131],"Mixture":[132],"Model":[133],"assumption.":[134],"We":[135,158],"conducted":[137],"theoretical":[138],"analyses":[139],"on":[144],"probability":[146],"estimation":[149],"error":[152],"gap":[153],"optimum.":[157],"also":[160],"implemented":[161],"extensive":[162],"experiments":[163,175],"both":[165],"synthetic":[166],"real-world":[168],"heterogeneity.":[170],"Theoretical":[171],"analysis":[172],"empirical":[174],"show":[176],"that":[177],"superior":[182],"P2P":[185],"counterparts,":[187],"it":[189],"achieves":[190],"better":[191],"performance":[192],"than":[193],"cluster":[196],"method.":[198],"even":[204],"extremely":[206],"low":[207],"communication":[208],"budgets.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":7}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2022-11-29T00:00:00"}