{"id":"https://openalex.org/W4313182496","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892211","title":"A Fair Federated Learning Framework With Reinforcement Learning","display_name":"A Fair Federated Learning Framework With Reinforcement Learning","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4313182496","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892211"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892211","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5101420085","display_name":"Yaqi Sun","orcid":"https://orcid.org/0009-0001-3961-7652"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqi Sun","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School,Shenzhen,China","Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105"]},{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032913967","display_name":"Shijing Si","orcid":"https://orcid.org/0000-0003-4346-2574"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijing Si","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]},{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074472751","display_name":"Jianzong Wang","orcid":"https://orcid.org/0000-0002-9237-4231"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzong Wang","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]},{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108047157","display_name":"Yuhan Dong","orcid":"https://orcid.org/0000-0001-5275-1787"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhan Dong","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School,Shenzhen,China","Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101766219","display_name":"Zhitao Zhu","orcid":"https://orcid.org/0000-0001-9063-7969"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhitao Zhu","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","Institude of Advanced Technology, University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]},{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]},{"raw_affiliation_string":"Institude of Advanced Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016038454","display_name":"Jing Xiao","orcid":"https://orcid.org/0000-0001-9615-4749"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Xiao","raw_affiliation_strings":["Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]},{"raw_affiliation_string":"Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9947999715805054,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8634771108627319},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8068949580192566},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6601946353912354},{"id":"https://openalex.org/keywords/gini-coefficient","display_name":"Gini coefficient","score":0.5771071910858154},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5754943490028381},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5409236550331116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.503825843334198},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4787815809249878},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47814950346946716},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.44117262959480286},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.41139280796051025},{"id":"https://openalex.org/keywords/inequality","display_name":"Inequality","score":0.12852713465690613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0785948634147644},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07162633538246155}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8634771108627319},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8068949580192566},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6601946353912354},{"id":"https://openalex.org/C2779206190","wikidata":"https://www.wikidata.org/wiki/Q162455","display_name":"Gini coefficient","level":4,"score":0.5771071910858154},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5754943490028381},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5409236550331116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.503825843334198},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4787815809249878},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47814950346946716},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.44117262959480286},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.41139280796051025},{"id":"https://openalex.org/C45555294","wikidata":"https://www.wikidata.org/wiki/Q28113351","display_name":"Inequality","level":2,"score":0.12852713465690613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0785948634147644},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07162633538246155},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C513380476","wikidata":"https://www.wikidata.org/wiki/Q5055020","display_name":"Economic inequality","level":3,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892211","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":51,"referenced_works":["https://openalex.org/W1909320841","https://openalex.org/W2100960835","https://openalex.org/W2155027007","https://openalex.org/W2541884796","https://openalex.org/W2547875792","https://openalex.org/W2750384547","https://openalex.org/W2889634868","https://openalex.org/W2912592113","https://openalex.org/W2914328083","https://openalex.org/W2946193510","https://openalex.org/W2972570881","https://openalex.org/W2981206218","https://openalex.org/W3021654819","https://openalex.org/W3038022836","https://openalex.org/W3047304572","https://openalex.org/W3118608800","https://openalex.org/W3129362180","https://openalex.org/W3134070916","https://openalex.org/W3134509799","https://openalex.org/W3134843574","https://openalex.org/W3135887273","https://openalex.org/W3154608090","https://openalex.org/W3167566559","https://openalex.org/W3173537849","https://openalex.org/W3182739741","https://openalex.org/W3189615907","https://openalex.org/W3190703008","https://openalex.org/W3193066552","https://openalex.org/W3196371845","https://openalex.org/W3196405711","https://openalex.org/W3213859843","https://openalex.org/W4287322665","https://openalex.org/W4288101682","https://openalex.org/W4289548211","https://openalex.org/W4297687186","https://openalex.org/W4299283926","https://openalex.org/W4318619660","https://openalex.org/W6639732818","https://openalex.org/W6683204974","https://openalex.org/W6729007826","https://openalex.org/W6729448088","https://openalex.org/W6743688258","https://openalex.org/W6758757267","https://openalex.org/W6762879059","https://openalex.org/W6767676916","https://openalex.org/W6768537144","https://openalex.org/W6769624030","https://openalex.org/W6773976177","https://openalex.org/W6787972765","https://openalex.org/W6791444617","https://openalex.org/W6802667569"],"related_works":["https://openalex.org/W2366815465","https://openalex.org/W2348303887","https://openalex.org/W2378211422","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W4295559186","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W4321353415","https://openalex.org/W2913146933"],"abstract_inverted_index":{"Federated":[0],"learning":[1,66],"(FL)":[2],"is":[3,122],"a":[4,11,17,35,64,73,113],"paradigm":[5],"where":[6],"many":[7,126],"clients":[8,33,106],"collaboratively":[9],"train":[10],"model":[12],"under":[13],"the":[14,22,89,99,117,139],"coordination":[15],"of":[16,51,91,105,141,157],"central":[18],"server,":[19],"while":[20],"keeping":[21],"training":[23],"data":[24,29],"locally":[25],"stored.":[26],"However,":[27],"heterogeneous":[28],"distributions":[30],"over":[31,134],"different":[32],"remain":[34],"challenge":[36],"to":[37,75,79,84,111,125,137],"mainstream":[38],"FL":[39,128],"algorithms,":[40],"which":[41,70],"may":[42],"cause":[43],"slow":[44],"convergence,":[45],"overall":[46,158],"performance":[47,52],"degradation":[48],"and":[49,102,161],"unfairness":[50],"across":[53],"clients.":[54,80],"To":[55],"address":[56],"these":[57],"problems,":[58],"in":[59,107,155],"this":[60],"study":[61],"we":[62,82,97],"propose":[63,83],"reinforcement":[65,118],"framework,":[67],"called":[68],"PG-FFL,":[69],"automatically":[71],"learns":[72],"policy":[74],"assign":[76],"aggregation":[77],"weights":[78],"Additionally,":[81],"utilize":[85],"Gini":[86,100],"coefficient":[87,101],"as":[88],"measure":[90],"fairness":[92,160],"for":[93,116],"FL.":[94],"More":[95],"importantly,":[96],"apply":[98],"validation":[103],"accuracy":[104],"each":[108],"communication":[109],"round":[110],"construct":[112],"reward":[114],"function":[115],"learning.":[119],"Our":[120],"PG-FFL":[121],"also":[123],"compatible":[124],"existing":[127],"algorithms.":[129],"We":[130],"conduct":[131],"extensive":[132],"experiments":[133],"diverse":[135],"datasets":[136],"verify":[138],"effectiveness":[140],"our":[142,149],"framework.":[143],"The":[144],"experimental":[145],"results":[146],"show":[147],"that":[148],"framework":[150],"can":[151],"outperform":[152],"baseline":[153],"methods":[154],"terms":[156],"performance,":[159],"convergence":[162],"speed.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
