{"id":"https://openalex.org/W7160283847","doi":"https://doi.org/10.1109/jiot.2026.3690200","title":"Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective","display_name":"Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective","publication_year":2026,"publication_date":"2026-05-04","ids":{"openalex":"https://openalex.org/W7160283847","doi":"https://doi.org/10.1109/jiot.2026.3690200"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3690200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3690200","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2605.09356","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001189882","display_name":"Akihito Taya","orcid":"https://orcid.org/0000-0001-9074-9709"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akihito Taya","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9074-9709","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046878953","display_name":"Yuuki Nishiyama","orcid":"https://orcid.org/0000-0002-5549-5595"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuuki Nishiyama","raw_affiliation_strings":["Center for Spatial Information Science, The University of Tokyo, Kashiwa-shi, Chiba, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5549-5595","affiliations":[{"raw_affiliation_string":"Center for Spatial Information Science, The University of Tokyo, Kashiwa-shi, Chiba, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050720322","display_name":"Kaoru Sezaki","orcid":"https://orcid.org/0000-0003-1194-4632"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kaoru Sezaki","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-1194-4632","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44701357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"14","first_page":"32240","last_page":"32254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9174000024795532,"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":0.9174000024795532,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.03319999948143959,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.004000000189989805,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.718999981880188},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.550000011920929},{"id":"https://openalex.org/keywords/convexity","display_name":"Convexity","score":0.531499981880188},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4681999981403351},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.45080000162124634},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.44859999418258667},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.445499986410141},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.41370001435279846},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.40459999442100525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8337000012397766},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.718999981880188},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.550000011920929},{"id":"https://openalex.org/C72134830","wikidata":"https://www.wikidata.org/wiki/Q5166524","display_name":"Convexity","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4681999981403351},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.45080000162124634},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43290001153945923},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.41370001435279846},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3456999957561493},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.33660000562667847},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C205875254","wikidata":"https://www.wikidata.org/wiki/Q17156857","display_name":"Decentralised system","level":3,"score":0.30640000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jiot.2026.3690200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3690200","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2605.09356","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.09356","pdf_url":"https://arxiv.org/pdf/2605.09356","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2605.09356","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.09356","pdf_url":"https://arxiv.org/pdf/2605.09356","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8530811665","display_name":"Active-Inference-Driven Cooperation Strategies in Sensor-Actuator Networks for Smart Environments","funder_award_id":"24K20759","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160283847.pdf","grobid_xml":"https://content.openalex.org/works/W7160283847.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Decentralized":[0],"federated":[1,31,98],"learning":[2,11,32],"(FL)":[3],"is":[4,60,72],"a":[5,140,155,162,180],"promising":[6],"approach":[7],"for":[8,79],"training":[9,71],"machine":[10],"models":[12],"on":[13],"sensor":[14],"networks,":[15],"Internet":[16],"of":[17,103,110,121],"Things":[18],"(IoT)":[19],"devices,":[20,52],"and":[21,45,75,150,188,201],"other":[22],"edge":[23],"systems":[24],"where":[25,173],"no":[26],"central":[27],"server":[28],"exists.":[29],"While":[30],"offers":[33],"advantages":[34],"such":[35],"as":[36,161],"preserving":[37],"data":[38,49,177],"privacy,":[39],"it":[40,160],"often":[41],"suffers":[42],"from":[43,154,178],"non-independent":[44],"identically":[46],"distributed":[47],"(IID)":[48],"distributions":[50],"across":[51],"which":[53,126],"cause":[54],"significant":[55],"performance":[56],"degradation.":[57],"This":[58],"issue":[59],"particularly":[61],"severe":[62,147],"when":[63],"directly":[64],"optimizing":[65],"model":[66],"parameters,":[67],"because":[68],"neural":[69],"network":[70],"inherently":[73],"non-convex":[74],"standard":[76],"convergence":[77,191],"guarantees":[78],"convex":[80],"optimization":[81],"do":[82],"not":[83],"apply.":[84],"Unlike":[85],"existing":[86,193],"decentralized":[87,194],"FL":[88,195],"methods":[89],"that":[90,184],"primarily":[91],"operate":[92],"in":[93],"parameter":[94,132],"space,":[95],"we":[96],"propose":[97],"function-space":[99],"alternating":[100,118],"direction":[101,119],"method":[102,120],"multipliers":[104,122],"(FedF-ADMM).":[105],"FedF-ADMM":[106,185],"exploits":[107],"the":[108,131],"convexity":[109],"loss":[111],"functionals":[112],"within":[113],"function":[114],"space":[115,133],"to":[116,143],"derive":[117],"(ADMM)-based":[123],"update":[124],"directions,":[125],"are":[127],"subsequently":[128],"projected":[129],"onto":[130],"via":[134],"knowledge":[135],"distillation.":[136],"We":[137],"further":[138],"introduce":[139],"stabilization":[141],"coefficient":[142],"enhance":[144],"robustness":[145],"under":[146,167],"non-IID":[148,169],"settings":[149,172],"analyze":[151],"its":[152],"behavior":[153],"control-theoretic":[156],"perspective":[157],"by":[158],"interpreting":[159],"proportional-integral":[163],"(PI)":[164],"term.":[165],"Experiments":[166],"challenging":[168],"scenarios,":[170],"including":[171],"each":[174],"device":[175],"has":[176],"only":[179],"single":[181],"label,":[182],"demonstrate":[183],"achieves":[186],"faster":[187],"more":[189],"stable":[190],"than":[192],"methods,":[196],"while":[197],"attaining":[198],"higher":[199],"accuracy":[200],"better":[202],"consensus":[203],"among":[204],"devices.":[205]},"counts_by_year":[],"updated_date":"2026-08-19T15:00:24.278416","created_date":"2026-05-06T00:00:00"}
