{"id":"https://openalex.org/W4400728495","doi":"https://doi.org/10.1109/jstsp.2024.3430118","title":"Federated Learning at Scale: Addressing Client Intermittency and Resource Constraints","display_name":"Federated Learning at Scale: Addressing Client Intermittency and Resource Constraints","publication_year":2024,"publication_date":"2024-07-17","ids":{"openalex":"https://openalex.org/W4400728495","doi":"https://doi.org/10.1109/jstsp.2024.3430118"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2024.3430118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2024.3430118","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","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/A5065598825","display_name":"M\u00f3nica Ribero","orcid":"https://orcid.org/0000-0002-9634-0880"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M\u00f3nica Ribero","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067602750","display_name":"Haris Vikalo","orcid":"https://orcid.org/0000-0002-7945-4114"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haris Vikalo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008917819","display_name":"Gustavo de Veciana","orcid":"https://orcid.org/0000-0002-1498-494X"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gustavo de Veciana","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065598825"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":0.683,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74251738,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"19","issue":"1","first_page":"60","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9894999861717224,"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":0.9894999861717224,"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":0.7319312691688538},{"id":"https://openalex.org/keywords/intermittency","display_name":"Intermittency","score":0.6652895212173462},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6008511185646057},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4872957468032837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4097156822681427},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.351714551448822},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18034547567367554}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7319312691688538},{"id":"https://openalex.org/C2780388094","wikidata":"https://www.wikidata.org/wiki/Q1666248","display_name":"Intermittency","level":3,"score":0.6652895212173462},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6008511185646057},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4872957468032837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4097156822681427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.351714551448822},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18034547567367554},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C196558001","wikidata":"https://www.wikidata.org/wiki/Q190132","display_name":"Turbulence","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstsp.2024.3430118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2024.3430118","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3382325400","display_name":null,"funder_award_id":"2148224","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2109690032","https://openalex.org/W2568437813","https://openalex.org/W2810950405","https://openalex.org/W2912213068","https://openalex.org/W2995022099","https://openalex.org/W3013730797","https://openalex.org/W3021654819","https://openalex.org/W3080934299","https://openalex.org/W3136022984","https://openalex.org/W3163584387","https://openalex.org/W3163739719","https://openalex.org/W4226262972","https://openalex.org/W4281753687","https://openalex.org/W4312875989","https://openalex.org/W4388818404","https://openalex.org/W6640396632","https://openalex.org/W6728757088","https://openalex.org/W6736057607","https://openalex.org/W6736413256","https://openalex.org/W6751961731","https://openalex.org/W6755988804","https://openalex.org/W6759226220","https://openalex.org/W6759238902","https://openalex.org/W6762028012","https://openalex.org/W6763070779","https://openalex.org/W6765541894","https://openalex.org/W6773817997","https://openalex.org/W6773976177","https://openalex.org/W6779269186","https://openalex.org/W6784048413","https://openalex.org/W6790212648","https://openalex.org/W6790640957","https://openalex.org/W6795281715","https://openalex.org/W6796096428","https://openalex.org/W6800899058","https://openalex.org/W6838903728"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0,23,127,193],"federated":[1,55,164,269],"learning":[2,11,56,165,224],"systems,":[3],"a":[4,17,31,99,200],"server":[5,29,90],"coordinates":[6],"the":[7,28,48,60,89,116,134,145,150,218,223,250],"training":[8,67],"of":[9,19,26,33,51,97,109,152,276,303],"machine":[10],"models":[12],"on":[13,140,176,266],"data":[14,142,168,305],"distributed":[15],"across":[16],"number":[18,96,151],"participating":[20],"client":[21,78,100,121,171,177,206,227],"devices.":[22],"each":[24],"round":[25,50,108],"training,":[27],"selects":[30],"subset":[32],"devices":[34],"to":[35,47,65,114,189,205,257,293],"perform":[36,66],"model":[37,119],"updates":[38,44],"and,":[39],"in":[40,73,86,104,149,274,301],"turn,":[41],"aggregates":[42],"those":[43],"before":[45],"proceeding":[46],"next":[49],"training.":[52,110],"Most":[53],"state-of-the-art":[54,251],"algorithms":[57],"assume":[58],"that":[59,185,203,231],"clients":[61,135,256],"are":[62,136],"always":[63,259],"available":[64,153],"\u2013":[68],"an":[69,93,160],"assumption":[70],"readily":[71],"violated":[72],"many":[74],"practical":[75],"settings":[76],"where":[77,88,133],"availability":[79,172,207],"is":[80],"intermittent":[81],"or":[82],"even":[83],"transient;":[84],"moreover,":[85],"systems":[87,132],"samples":[91],"from":[92],"exceedingly":[94],"large":[95],"clients,":[98],"will":[101],"likely":[102],"participate":[103],"at":[105,243],"most":[106],"one":[107],"This":[111],"can":[112],"lead":[113],"biasing":[115],"learned":[117],"global":[118],"towards":[120],"groups":[122,146],"endowed":[123],"with":[124,240],"more":[125],"resources.":[126],"this":[128],"paper,":[129],"we":[130],"consider":[131],"naturally":[137],"grouped":[138],"based":[139],"their":[141],"distributions,":[143,169],"and":[144,173,209,271,282,295],"exhibit":[147],"variations":[148],"clients.":[154],"We":[155,229,261],"present":[156],"<sc":[157,195,236,263,279,283,288],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[158,196,237,245,264,280,284,289],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Flics-opt</small>,":[159],"algorithm":[161],"for":[162,232],"large-scale":[163],"over":[166],"heterogeneous":[167,304],"time-varying":[170],"further":[174],"constraints":[175],"participation":[178,215],"reflecting,":[179],"e.g.,":[180],"overall":[181],"energy":[182],"efficiency":[183],"objectives":[184],"should":[186],"be":[187,258],"met":[188],"achieve":[190],"sustainable":[191],"deployment.":[192],"particular,":[194],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Flics-opt</small>":[197,238,265],"dynamically":[198],"learns":[199],"selection":[201],"policy":[202],"adapts":[204],"patterns":[208],"communication":[210],"constraints,":[211],"ensuring":[212],"per-group":[213],"long-term":[214],"which":[216,254],"minimizes":[217],"variance":[219],"inevitably":[220],"introduced":[221],"into":[222],"process":[225],"by":[226,291],"sampling.":[228],"show":[230,272],"non-convex":[233],"smooth":[234],"functions":[235],"coupled":[239],"SGD":[241],"converges":[242],"<inline-formula":[244],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[246],"notation=\"LaTeX\">$O(1/\\sqrt{T})$</tex-math></inline-formula>":[247],"rate,":[248],"matching":[249],"convergence":[252],"results":[253],"require":[255],"available.":[260],"test":[262],"three":[267],"realistic":[268],"datasets":[270],"that,":[273],"terms":[275],"maximum":[277],"accuracy,":[278],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Flics-Avg</small>":[281],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Flics-Adam</small>":[285],"outperform":[286],"traditional":[287],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">FedAvg</small>":[290],"up":[292],"280%":[294],"60%,":[296],"respectively,":[297],"while":[298],"exhibiting":[299],"robustness":[300],"face":[302],"distributions.":[306]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}