{"id":"https://openalex.org/W4282971512","doi":"https://doi.org/10.1145/3544495","title":"AggEnhance: Aggregation Enhancement by Class Interior Points in Federated Learning with Non-IID Data","display_name":"AggEnhance: Aggregation Enhancement by Class Interior Points in Federated Learning with Non-IID Data","publication_year":2022,"publication_date":"2022-06-16","ids":{"openalex":"https://openalex.org/W4282971512","doi":"https://doi.org/10.1145/3544495"},"language":"en","primary_location":{"id":"doi:10.1145/3544495","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3544495","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3544495","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3544495","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051639592","display_name":"Jinxiang Ou","orcid":"https://orcid.org/0000-0001-8002-9302"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinxiang Ou","raw_affiliation_strings":["Tsinghua University, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8002-9302","affiliations":[{"raw_affiliation_string":"Tsinghua University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009179731","display_name":"Yunheng Shen","orcid":"https://orcid.org/0000-0003-1961-0274"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunheng Shen","raw_affiliation_strings":["Tsinghua University, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1961-0274","affiliations":[{"raw_affiliation_string":"Tsinghua University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029738971","display_name":"Feng Wang","orcid":"https://orcid.org/0000-0001-7553-3184"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wang","raw_affiliation_strings":["Tsinghua University, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7553-3184","affiliations":[{"raw_affiliation_string":"Tsinghua University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393711","display_name":"Qiao Liu","orcid":"https://orcid.org/0000-0002-9781-3360"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiao Liu","raw_affiliation_strings":["Stanford University, Stanford, California, USA"],"raw_orcid":"https://orcid.org/0000-0002-9781-3360","affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, California, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081242795","display_name":"Xuegong Zhang","orcid":"https://orcid.org/0000-0002-9684-5643"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuegong Zhang","raw_affiliation_strings":["Tsinghua University, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9684-5643","affiliations":[{"raw_affiliation_string":"Tsinghua University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074195858","display_name":"Hairong Lv","orcid":"https://orcid.org/0000-0003-1568-6861"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hairong Lv","raw_affiliation_strings":["Tsinghua University, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1568-6861","affiliations":[{"raw_affiliation_string":"Tsinghua University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1809,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81726325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"13","issue":"6","first_page":"1","last_page":"25"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9495000243186951,"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":0.8945156931877136},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6687281131744385},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5306923389434814},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.48418620228767395},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.46786975860595703},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46528974175453186},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4587564468383789},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34933024644851685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3365861177444458},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32549020648002625},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.09498018026351929}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8945156931877136},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6687281131744385},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5306923389434814},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.48418620228767395},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.46786975860595703},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46528974175453186},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4587564468383789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34933024644851685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3365861177444458},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32549020648002625},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.09498018026351929},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3544495","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3544495","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3544495","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3544495","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3544495","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3544495","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3818908246","display_name":null,"funder_award_id":"42050101 and 61721003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5814160623","display_name":null,"funder_award_id":"61721003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G989809018","display_name":null,"funder_award_id":"42050101","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4282971512.pdf","grobid_xml":"https://content.openalex.org/works/W4282971512.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2031489346","https://openalex.org/W2041616772","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2807006176","https://openalex.org/W2896422817","https://openalex.org/W2900120080","https://openalex.org/W2917462349","https://openalex.org/W2949505878","https://openalex.org/W2963819344","https://openalex.org/W2972570881","https://openalex.org/W2975985894","https://openalex.org/W2996974038","https://openalex.org/W3012501605","https://openalex.org/W3033511014","https://openalex.org/W3038022836","https://openalex.org/W3086152015","https://openalex.org/W3086590218","https://openalex.org/W4212774754","https://openalex.org/W4250482878","https://openalex.org/W4287906413","https://openalex.org/W6752029299","https://openalex.org/W6755988804","https://openalex.org/W6759238902","https://openalex.org/W6759853437","https://openalex.org/W6768035077","https://openalex.org/W6782937392"],"related_works":["https://openalex.org/W1663079876","https://openalex.org/W2069133146","https://openalex.org/W2017545316","https://openalex.org/W2100576949","https://openalex.org/W2793666424","https://openalex.org/W2159686533","https://openalex.org/W4242339654","https://openalex.org/W2349160795","https://openalex.org/W2100057527","https://openalex.org/W2809456908"],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"is":[3,13,142,213],"a":[4,28,60,65,75,85,97],"privacy-preserving":[5],"paradigm":[6],"for":[7,90,152,190,196],"multi-institutional":[8],"collaborations,":[9],"where":[10,94],"the":[11,20,32,40,45,50,54,92,103,108,124,130,136,143,153,174,184,191,197,231,235,240,245],"aggregation":[12,24,154],"an":[14,149],"essential":[15],"procedure":[16],"after":[17],"training":[18],"on":[19,111,163,188],"local":[21,55,104,232],"datasets.":[22],"Conventional":[23],"algorithms":[25],"often":[26],"apply":[27,216],"weighted":[29],"averaging":[30],"of":[31,99,132,138,161,173,209],"updates":[33,56],"generated":[34],"from":[35,102,230],"distributed":[36],"machines":[37],"to":[38,59,73,146,215,217,234],"update":[39],"global":[41,236],"model.":[42],"However,":[43],"while":[44],"data":[46,165,228],"distributions":[47],"are":[48],"non-IID,":[49],"large":[51],"discrepancy":[52],"between":[53],"might":[57],"lead":[58],"poor":[61],"averaged":[62],"result":[63,110],"and":[64,106,194],"lower":[66],"convergence":[67,175],"speed,":[68],"i.e.,":[69],"more":[70],"iterations":[71,185],"required":[72],"achieve":[74],"certain":[76],"performance.":[77],"To":[78,135],"solve":[79],"this":[80,82,121,141],"problem,":[81],"article":[83],"proposes":[84],"novel":[86],"method":[87,151,169,203],"named":[88,115],"AggEnhance":[89],"enhancing":[91,150],"aggregation,":[93],"we":[95],"synthesize":[96],"group":[98],"reliable":[100],"samples":[101],"models":[105],"tune":[107],"aggregated":[109,133],"them.":[112],"These":[113],"samples,":[114],"class":[116],"interior":[117],"points":[118],"(CIPs)":[119],"in":[120,155,176],"work,":[122],"bound":[123],"relevant":[125],"decision":[126],"boundaries":[127],"that":[128,167],"ensure":[129],"performance":[131],"result.":[134],"best":[137],"our":[139,168,181,202],"knowledge,":[140],"first":[144],"work":[145],"explicitly":[147],"design":[148],"prevailing":[156],"FL":[157,210,220,247],"pipelines.":[158],"A":[159],"series":[160],"experiments":[162],"real":[164],"demonstrate":[166],"has":[170],"noticeable":[171],"improvements":[172],"non-IID":[177],"scenarios.":[178],"In":[179],"particular,":[180],"approach":[182],"reduces":[183],"by":[186],"31.87%":[187],"average":[189],"CIFAR10":[192],"dataset":[193],"43.90%":[195],"PASCAL":[198],"VOC":[199],"dataset.":[200],"Since":[201],"does":[204,224],"not":[205,225],"modify":[206],"other":[207],"procedures":[208],"pipelines,":[211],"it":[212,223],"easy":[214],"most":[218],"existing":[219],"frameworks.":[221],"Furthermore,":[222],"require":[226],"additional":[227],"transmitted":[229],"clients":[233],"server,":[237],"thus":[238],"holding":[239],"same":[241],"security":[242],"level":[243],"as":[244],"original":[246],"algorithms.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}