{"id":"https://openalex.org/W4313158119","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892624","title":"Cali3F: Calibrated Fast Fair Federated Recommendation System","display_name":"Cali3F: Calibrated Fast Fair Federated Recommendation System","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4313158119","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892624"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892624","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":"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/A5101766219","display_name":"Zhitao Zhu","orcid":"https://orcid.org/0000-0001-9063-7969"},"institutions":[{"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"]},{"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"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhitao Zhu","raw_affiliation_strings":["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"]}]},{"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"],"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"]}]},{"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/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzong Wang","raw_affiliation_strings":["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"]}]},{"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"],"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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101766219"],"corresponding_institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4401726822"],"apc_list":null,"apc_paid":null,"fwci":1.5599,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.85463699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9930999875068665,"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"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9847999811172485,"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":0.8737269639968872},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.7437066435813904},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7384575009346008},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6842017769813538},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6425187587738037},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6149929761886597},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.589650571346283},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5582119822502136},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.43778523802757263},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4140612483024597},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39478254318237305},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.37059903144836426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33899158239364624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8737269639968872},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7437066435813904},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7384575009346008},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6842017769813538},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6425187587738037},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6149929761886597},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.589650571346283},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5582119822502136},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.43778523802757263},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4140612483024597},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39478254318237305},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.37059903144836426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33899158239364624},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892624","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":[{"display_name":"Peace, Justice and strong institutions","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2025605741","https://openalex.org/W2605350416","https://openalex.org/W2783792211","https://openalex.org/W2912213068","https://openalex.org/W2912592113","https://openalex.org/W2913777072","https://openalex.org/W2946193510","https://openalex.org/W2955213239","https://openalex.org/W2995022099","https://openalex.org/W3018464563","https://openalex.org/W3021654819","https://openalex.org/W3047789363","https://openalex.org/W3064112253","https://openalex.org/W3080934299","https://openalex.org/W3081273427","https://openalex.org/W3091635927","https://openalex.org/W3092408317","https://openalex.org/W3099314130","https://openalex.org/W3125494587","https://openalex.org/W3129362180","https://openalex.org/W3161357657","https://openalex.org/W3174074918","https://openalex.org/W3193107436","https://openalex.org/W3200755887","https://openalex.org/W3201463768","https://openalex.org/W4213390626","https://openalex.org/W4229012946","https://openalex.org/W4285762978","https://openalex.org/W4297687186","https://openalex.org/W4300427714","https://openalex.org/W4318619660","https://openalex.org/W4391620832","https://openalex.org/W6728757088","https://openalex.org/W6729007826","https://openalex.org/W6738383168","https://openalex.org/W6747546636","https://openalex.org/W6758757267","https://openalex.org/W6762879059","https://openalex.org/W6765541894","https://openalex.org/W6779174293","https://openalex.org/W6784312123","https://openalex.org/W6784336702","https://openalex.org/W6786597537","https://openalex.org/W6791444617","https://openalex.org/W6800024925","https://openalex.org/W7006383079"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"The":[0],"increasingly":[1],"stringent":[2],"regulations":[3],"on":[4],"privacy":[5],"protection":[6],"have":[7,43],"sparked":[8],"interest":[9],"in":[10,96,104,190],"federated":[11,40,69,112,147],"learning.":[12],"As":[13],"a":[14,26,110,126,142,158],"distributed":[15],"machine":[16],"learning":[17],"framework,":[18],"it":[19],"bridges":[20],"isolated":[21],"data":[22,33,88],"islands":[23],"by":[24,157,168],"training":[25,115,133],"global":[27,174],"model":[28],"over":[29],"devices":[30],"while":[31],"keeping":[32],"localized.":[34],"Specific":[35],"to":[36,46,63,73,87,117,130,192],"recommendation":[37,41,78,113,120,148],"systems,":[38],"many":[39],"algorithms":[42],"been":[44],"proposed":[45,140],"realize":[47],"the":[48,75,83,97,119,132,136,154,173,178,188],"privacy-preserving":[49],"collaborative":[50],"recommendation.":[51],"However,":[52],"several":[53],"constraints":[54],"remain":[55],"largely":[56],"unexplored.":[57],"One":[58],"big":[59],"concern":[60],"is":[61],"how":[62],"ensure":[64],"fairness":[65,167],"between":[66],"participants":[67],"of":[68,77,180],"learning,":[70],"that":[71],"is,":[72],"maintain":[74],"uniformity":[76],"performance":[79,121,179],"across":[80,182],"devices.":[81],"On":[82],"other":[84],"hand,":[85],"due":[86],"heterogeneity":[89],"and":[90,145,186],"limited":[91],"networks,":[92],"additional":[93],"challenges":[94],"occur":[95],"convergence":[98,155],"speed.":[99],"To":[100],"address":[101],"these":[102],"problems,":[103],"this":[105],"paper,":[106],"we":[107,124,139],"first":[108],"propose":[109],"personalized":[111],"system":[114],"algorithm":[116],"improve":[118],"fairness.":[122],"Then":[123],"adopt":[125],"clustering-based":[127],"aggregation":[128,194],"method":[129],"accelerate":[131],"process.":[134],"Combining":[135],"two":[137],"components,":[138],"Cali3F,":[141],"calibrated":[143],"fast":[144],"fair":[146],"framework.":[149],"Cali3F":[150,181],"not":[151],"only":[152],"addresses":[153],"problem":[156],"within-cluster":[159],"parameter":[160],"sharing":[161],"approach":[162],"but":[163],"also":[164],"significantly":[165],"boosts":[166],"calibrating":[169],"local":[170],"models":[171],"with":[172],"model.":[175],"We":[176],"demonstrate":[177],"standard":[183],"benchmark":[184],"datasets":[185],"explore":[187],"efficacy":[189],"comparison":[191],"traditional":[193],"approaches.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
