{"id":"https://openalex.org/W4360604929","doi":"https://doi.org/10.1109/icaiic57133.2023.10066985","title":"A Performance Efficient Approach of Global Training in Federated Learning","display_name":"A Performance Efficient Approach of Global Training in Federated Learning","publication_year":2023,"publication_date":"2023-02-20","ids":{"openalex":"https://openalex.org/W4360604929","doi":"https://doi.org/10.1109/icaiic57133.2023.10066985"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic57133.2023.10066985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic57133.2023.10066985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5060293559","display_name":"Dost Muhammad Saqib Bhatti","orcid":"https://orcid.org/0000-0002-0204-8484"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dost Muhammad Saqib Bhatti","raw_affiliation_strings":["Hanyang University,Department of Electrical and Electronic Engineering,Ansan,South Korea","Department of Electrical and Electronic Engineering, Hanyang University, Ansan, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Electrical and Electronic Engineering,Ansan,South Korea","institution_ids":["https://openalex.org/I4575257"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Hanyang University, Ansan, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014061593","display_name":"Haewoon Nam","orcid":"https://orcid.org/0000-0001-9847-7023"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Haewoon Nam","raw_affiliation_strings":["Hanyang University,Department of Electrical and Electronic Engineering,Ansan,South Korea","Department of Electrical and Electronic Engineering, Hanyang University, Ansan, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Electrical and Electronic Engineering,Ansan,South Korea","institution_ids":["https://openalex.org/I4575257"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Hanyang University, Ansan, South Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060293559"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":1.049,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80320342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"112","last_page":"115"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8484868407249451},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6974467635154724},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.6954156160354614},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5829782485961914},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5730825662612915},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4647964835166931},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4205596148967743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4064192771911621},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38908851146698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8484868407249451},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6974467635154724},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6954156160354614},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5829782485961914},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5730825662612915},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4647964835166931},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4205596148967743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4064192771911621},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38908851146698},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic57133.2023.10066985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic57133.2023.10066985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2807006176","https://openalex.org/W2903471046","https://openalex.org/W2949505878","https://openalex.org/W2980216952","https://openalex.org/W2981298997","https://openalex.org/W2989289980","https://openalex.org/W2998045710","https://openalex.org/W3006017224","https://openalex.org/W3033403733","https://openalex.org/W3038022836","https://openalex.org/W3089562172","https://openalex.org/W3101718285","https://openalex.org/W3176364684","https://openalex.org/W3186051974","https://openalex.org/W3214347624","https://openalex.org/W3215194618","https://openalex.org/W4226101686","https://openalex.org/W4226142397","https://openalex.org/W4287332481","https://openalex.org/W4309997752","https://openalex.org/W6677186076","https://openalex.org/W6695838908","https://openalex.org/W6743688258","https://openalex.org/W6752029299","https://openalex.org/W6757139170","https://openalex.org/W6769627709","https://openalex.org/W6783615279"],"related_works":["https://openalex.org/W4298221930","https://openalex.org/W230091440","https://openalex.org/W3004218185","https://openalex.org/W4390241083","https://openalex.org/W2777914285","https://openalex.org/W2233261550","https://openalex.org/W4245457074","https://openalex.org/W4394050964","https://openalex.org/W4385893187","https://openalex.org/W2551249631"],"abstract_inverted_index":{"Federated":[0],"learning":[1,161],"is":[2,26,69,82,155],"a":[3,119,131],"novel":[4],"approach":[5,135,154],"of":[6,19,66,93,110,116,125],"training":[7,38,68],"the":[8,12,16,20,36,50,54,61,76,79,89,108,112,123,141,148,158],"global":[9,62,67,126],"model":[10,92],"on":[11,122],"server":[13],"by":[14],"utilizing":[15],"personal":[17],"data":[18,24,81,142],"end":[21],"users":[22,29],"while":[23],"privacy":[25],"preserved.":[27],"The":[28,152],"called":[30],"clients":[31,117,145],"are":[32,57],"required":[33],"to":[34,49,59,103],"perform":[35],"local":[37,41,47,55,91,114,150],"using":[39],"their":[40],"datasets":[42],"and":[43,84,163],"forward":[44],"those":[45],"trained":[46],"models":[48,56,115],"server,":[51],"in":[52],"which":[53,139],"aggregated":[58],"update":[60],"model.":[63],"This":[64,128],"process":[65,109],"carried":[70],"out":[71],"for":[72,136],"several":[73],"rounds":[74],"until":[75],"convergence.":[77],"Practically,":[78],"clients'":[80],"non-independent":[83],"identically":[85],"distributed":[86],"(Non-IID).":[87],"Hence,":[88,107],"updated":[90],"each":[94],"client":[95,101],"may":[96],"vary":[97],"from":[98],"every":[99],"other":[100],"due":[102],"heterogeneity":[104,143],"among":[105,144],"them.":[106],"aggregating":[111,147],"diversified":[113],"has":[118],"huge":[120],"impact":[121],"performance":[124,132],"training.":[127],"article":[129],"proposes":[130],"efficient":[133],"aggregation":[134],"federated":[137,160],"learning,":[138],"considers":[140],"before":[146],"received":[149],"models.":[151],"proposed":[153],"compared":[156],"with":[157],"conventional":[159],"methods,":[162],"it":[164],"achieves":[165],"improved":[166],"performance.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
