{"id":"https://openalex.org/W4206220619","doi":"https://doi.org/10.1109/tai.2021.3133816","title":"Federated Multitask Learning for HyperFace","display_name":"Federated Multitask Learning for HyperFace","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4206220619","doi":"https://doi.org/10.1109/tai.2021.3133816"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2021.3133816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2021.3133816","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Artificial Intelligence","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/A5100374160","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0003-0939-4352"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083468753","display_name":"Hang Bai","orcid":"https://orcid.org/0000-0002-6871-3694"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Bai","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383751","display_name":"Yonggang Zhang","orcid":"https://orcid.org/0000-0003-4548-1111"},"institutions":[{"id":"https://openalex.org/I4210104453","display_name":"Shaanxi Science and Technology Department","ror":"https://ror.org/01c2sx728","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210104453","https://openalex.org/I4210120069","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonggang Zhang","raw_affiliation_strings":["Shaanxi Province Science and Technology Resources Coordination Center, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"Shaanxi Province Science and Technology Resources Coordination Center, Xi’an, China","institution_ids":["https://openalex.org/I4210104453"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054884083","display_name":"Xinyi Niu","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi Niu","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101538432","display_name":"Bin Yu","orcid":"https://orcid.org/0000-0003-3794-1069"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yu","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011958968","display_name":"Yuan Gao","orcid":"https://orcid.org/0000-0002-2990-9205"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Gao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000102478","display_name":"Yu Xie","orcid":"https://orcid.org/0000-0002-3431-0432"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Xie","raw_affiliation_strings":["Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100374160"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.6799,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76660875,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":"5","first_page":"788","last_page":"797"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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":0.9998000264167786,"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/T11448","display_name":"Face recognition and analysis","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9726999998092651,"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/multi-task-learning","display_name":"Multi-task learning","score":0.8459265232086182},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8097227811813354},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5937714576721191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5855668783187866},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.5687183141708374},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5598670244216919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5424838662147522},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4688820540904999},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42662787437438965},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.262444406747818}],"concepts":[{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.8459265232086182},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8097227811813354},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5937714576721191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5855668783187866},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.5687183141708374},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5598670244216919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5424838662147522},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4688820540904999},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42662787437438965},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.262444406747818},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2021.3133816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2021.3133816","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8946654418","display_name":null,"funder_award_id":"62106131","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":52,"referenced_works":["https://openalex.org/W1614862348","https://openalex.org/W1986744686","https://openalex.org/W1994348297","https://openalex.org/W2012885984","https://openalex.org/W2018096278","https://openalex.org/W2025198378","https://openalex.org/W2031250362","https://openalex.org/W2047508432","https://openalex.org/W2053637704","https://openalex.org/W2065180801","https://openalex.org/W2083842231","https://openalex.org/W2431832508","https://openalex.org/W2526425061","https://openalex.org/W2530417694","https://openalex.org/W2535838896","https://openalex.org/W2587770880","https://openalex.org/W2588595876","https://openalex.org/W2606065148","https://openalex.org/W2742912327","https://openalex.org/W2753709519","https://openalex.org/W2784199143","https://openalex.org/W2791777119","https://openalex.org/W2798720628","https://openalex.org/W2889964863","https://openalex.org/W2890956466","https://openalex.org/W2891076394","https://openalex.org/W2912213068","https://openalex.org/W2913340405","https://openalex.org/W2942392852","https://openalex.org/W2959784504","https://openalex.org/W2962786991","https://openalex.org/W2962788286","https://openalex.org/W2962824366","https://openalex.org/W2963191611","https://openalex.org/W2963318081","https://openalex.org/W2963377935","https://openalex.org/W2963430933","https://openalex.org/W3002514492","https://openalex.org/W3008193129","https://openalex.org/W3019286073","https://openalex.org/W3027859434","https://openalex.org/W3105122387","https://openalex.org/W3123459983","https://openalex.org/W3173670432","https://openalex.org/W4318619660","https://openalex.org/W6629935912","https://openalex.org/W6677419484","https://openalex.org/W6679393576","https://openalex.org/W6683474303","https://openalex.org/W6728757088","https://openalex.org/W6732298257","https://openalex.org/W6738383168"],"related_works":["https://openalex.org/W4317941881","https://openalex.org/W4398164851","https://openalex.org/W3035996294","https://openalex.org/W4229067761","https://openalex.org/W4323521275","https://openalex.org/W4220738117","https://openalex.org/W3091296419","https://openalex.org/W2954034773","https://openalex.org/W4322741898","https://openalex.org/W3159168343"],"abstract_inverted_index":{"Multitask":[0],"learning":[1,9,121,126,188],"(MTL)":[2],"is":[3,102,190,194],"a":[4,32,54,58,69,116,130,185],"promising":[5],"field":[6],"in":[7,37,53,68,84,93,129,133,167,242,249],"machine":[8,50],"owing":[10],"to":[11,14,103,127,135,144,175],"its":[12],"capability":[13],"improve":[15],"the":[16,26,38,45,72,82,94,105,137,147,150,156,176,208,212,220,230,243,250,256],"generalization":[17],"performance":[18],"of":[19,35,48,81,100,107,149,222,232,258],"all":[20,155],"tasks":[21],"by":[22],"sharing":[23],"knowledge":[24],"among":[25],"related":[27],"tasks.":[28],"MTL":[29,52,63,101,128,138,151],"has":[30],"attracted":[31],"large":[33],"amount":[34],"attention":[36],"multitask-related":[39],"community.":[40],"In":[41,111,153,202],"recent":[42],"years,":[43],"with":[44],"rapid":[46],"development":[47],"distributed":[49,55,70,85,95,131],"learning,":[51],"environment":[56,132],"becomes":[57],"hot":[59],"research":[60],"topic.":[61],"Although":[62],"can":[64,206],"reap":[65],"great":[66],"fruit":[67],"environment,":[71],"sensitive":[73,108],"information,":[74],"such":[75],"as":[76],"photos":[77],"and":[78,143,169,214,246],"voice":[79],"recordings":[80],"owner,":[83],"data":[86],"may":[87],"be":[88],"leaked":[89,142],"during":[90],"training.":[91],"Consequently,":[92],"settings,":[96],"one":[97],"prominent":[98],"challenge":[99],"prevent":[104],"disclosure":[106],"private":[109],"data.":[110,201],"this":[112,203],"article,":[113],"we":[114],"propose":[115],"novel":[117],"approach,":[118],"federated":[119,125],"multitask":[120],"(FMTL),":[122],"which":[123],"applies":[124],"order":[134],"protect":[136],"model":[139,173],"from":[140,229],"being":[141],"better":[145],"optimize":[146],"utility":[148,213],"model.":[152],"FMTL,":[154],"participants":[157,216],"independently":[158],"train":[159],"their":[160,164,172,187,198,223],"local":[161],"models":[162,231],"on":[163,197,238],"own":[165,199,224],"dataset":[166],"parallel":[168],"only":[170,196,218],"transmit":[171],"updates":[174],"central":[177],"server":[178],"for":[179],"aggregation":[180],"at":[181],"every":[182],"epoch.":[183],"As":[184],"result,":[186],"accuracy":[189],"enhanced":[191],"beyond":[192],"what":[193],"achieved":[195],"training":[200],"manner,":[204],"it":[205],"achieve":[207],"best":[209],"tradeoff":[210],"between":[211],"privacy:":[215],"not":[217],"preserve":[219],"privacy":[221],"data,":[225],"but":[226],"also":[227],"benefit":[228],"other":[233],"participants.":[234],"The":[235],"experimental":[236],"results":[237],"annotated":[239,247],"facial":[240],"landmarks":[241],"wild":[244,251],"(AFLW)":[245],"faces":[248],"(AFW)":[252],"benchmark":[253],"datasets":[254],"verify":[255],"effectiveness":[257],"our":[259],"framework.":[260]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}