{"id":"https://openalex.org/W7135072590","doi":"https://doi.org/10.1109/camsap66162.2025.11423983","title":"Convergence Of Agnostic Federated Averaging","display_name":"Convergence Of Agnostic Federated Averaging","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7135072590","doi":"https://doi.org/10.1109/camsap66162.2025.11423983"},"language":null,"primary_location":{"id":"doi:10.1109/camsap66162.2025.11423983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap66162.2025.11423983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 10th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","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/A5128814909","display_name":"Herlock SeyedAbolfazl Rahimi","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Herlock SeyedAbolfazl Rahimi","raw_affiliation_strings":["Yale University,Department of ECE"],"affiliations":[{"raw_affiliation_string":"Yale University,Department of ECE","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128827792","display_name":"Dionysis Kalogerias","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dionysis Kalogerias","raw_affiliation_strings":["Yale University,Department of ECE"],"affiliations":[{"raw_affiliation_string":"Yale University,Department of ECE","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5128814909"],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79830064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10772","display_name":"Distributed systems and fault tolerance","score":0.25380000472068787,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10772","display_name":"Distributed systems and fault tolerance","score":0.25380000472068787,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.06689999997615814,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10237","display_name":"Cryptography and Data Security","score":0.058400001376867294,"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/convergence","display_name":"Convergence (economics)","score":0.7343000173568726},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.6664000153541565},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5745000243186951},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.42149999737739563},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.41620001196861267},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.37549999356269836},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.3330000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7427999973297119},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.7343000173568726},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6664000153541565},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5745000243186951},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3912999927997589},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34790000319480896},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.3330000042915344},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3098999857902527},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/camsap66162.2025.11423983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap66162.2025.11423983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 10th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6473700404167175,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0,77],"learning":[1],"(FL)":[2],"enables":[3],"decentralized":[4],"model":[5],"training":[6],"without":[7,128],"centralizing":[8],"raw":[9],"data.":[10],"However,":[11],"practical":[12],"FL":[13],"deployments":[14],"often":[15],"face":[16],"a":[17,98],"key":[18],"realistic":[19],"challenge:":[20],"Clients":[21],"participate":[22],"intermittently":[23],"in":[24,56,141],"server":[25],"aggregation":[26,110,148],"and":[27,87],"with":[28,152],"unknown,":[29],"possibly":[30,94],"biased":[31],"participation":[32,132,156],"probabilities.":[33],"Most":[34],"existing":[35],"convergence":[36,91,117],"results":[37],"either":[38],"assume":[39],"fulldevice":[40],"participation,":[41,127],"or":[42],"rely":[43],"on":[44],"knowledge":[45,129,154],"of":[46,73,101,130,155],"(in":[47],"fact":[48,142],"uniform)":[49],"client":[50,85,126],"availability":[51],"distributions-assumptions":[52],"that":[53,66,138],"rarely":[54],"hold":[55],"practice.":[57],"In":[58],"this":[59],"work,":[60],"we":[61],"characterize":[62],"the":[63,70,74,109,115,131],"optimization":[64],"problem":[65],"consistently":[67],"adheres":[68],"to":[69],"stochastic":[71,125],"dynamics":[72],"well-known":[75],"agnostic":[76,120,139],"Averaging":[78],"(FedAvg)":[79],"algorithm":[80],"under":[81,122],"random":[82],"(and":[83,145],"variably-sized)":[84],"availability,":[86],"rigorously":[88],"establish":[89],"its":[90],"for":[92,119],"convex,":[93],"nonsmooth":[95],"losses,":[96],"achieving":[97],"standard":[99],"rate":[100],"order":[102],"$\\mathcal{O}(1":[103],"/":[104],"\\sqrt{T})$,":[105],"where":[106],"T":[107],"denotes":[108],"horizon.":[111],"Our":[112],"analysis":[113],"provides":[114],"first":[116],"guarantees":[118],"FedAvg":[121,140,149],"general,":[123],"non-uniform,":[124],"distribution.":[133],"We":[134],"also":[135],"empirically":[136],"demonstrate":[137],"outperforms":[143],"common":[144],"suboptimal)":[146],"weighted":[147],"variants,":[150],"even":[151],"server-side":[153],"weights.":[157]},"counts_by_year":[],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2026-03-13T00:00:00"}
