{"id":"https://openalex.org/W4312875989","doi":"https://doi.org/10.1109/jstsp.2022.3224590","title":"Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints","display_name":"Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints","publication_year":2022,"publication_date":"2022-11-24","ids":{"openalex":"https://openalex.org/W4312875989","doi":"https://doi.org/10.1109/jstsp.2022.3224590"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2022.3224590","doi":"https://doi.org/10.1109/jstsp.2022.3224590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2022.3224590","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,"listed_in":["anvur-scientific","cwts-core","dongbi-b","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2205.06730","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065598825","display_name":"M\u00f3nica Ribero","orcid":"https://orcid.org/0000-0002-9634-0880","observed_orcids":["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":false,"raw_author_name":"Monica Ribero","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-9634-0880","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","observed_orcids":["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"],"raw_orcid":"https://orcid.org/0000-0002-7945-4114","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 A. De Veciana","orcid":"https://orcid.org/0000-0002-1498-494X","observed_orcids":["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"],"raw_orcid":"https://orcid.org/0000-0002-1498-494X","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":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":3.4057,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":{"value":0.94127523,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":"17","issue":"1","first_page":"98","last_page":"111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994999766349792,"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":0.9994999766349792,"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":0.0003000000142492354,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":9.999999747378752e-05,"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/federated-learning","display_name":"federated learning","score":0.996999979019165},{"id":"https://openalex.org/keywords/adaptive-client-selection","display_name":"adaptive client selection","score":0.7620000243186951},{"id":"https://openalex.org/keywords/convergence","display_name":"convergence","score":0.33799999952316284},{"id":"https://openalex.org/keywords/fedavg","display_name":"FedAvg","score":0.5730000138282776},{"id":"https://openalex.org/keywords/edge-devices","display_name":"edge devices","score":0.5370000004768372}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8471817970275879},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.733063280582428},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6731408834457397},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6518450379371643},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6366875767707825},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6013811826705933},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4570688009262085},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.43844541907310486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4289938807487488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4097924828529358},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.38621237874031067},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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":3,"locations":[{"id":"doi:10.1109/jstsp.2022.3224590","doi":"https://doi.org/10.1109/jstsp.2022.3224590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2022.3224590","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,"listed_in":["anvur-scientific","cwts-core","dongbi-b","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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"},{"id":"pmh:oai:arXiv.org:2205.06730","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.06730","pdf_url":"https://arxiv.org/pdf/2205.06730","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,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.2205.06730","doi":"https://doi.org/10.48550/arxiv.2205.06730","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2205.06730","pdf_url":null,"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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2205.06730","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.06730","pdf_url":"https://arxiv.org/pdf/2205.06730","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,"listed_in":[],"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":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3382325400","display_name":"RINGS: Scalable and Resilient Networked Learning Systems","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"},{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312875989.pdf","grobid_xml":"https://content.openalex.org/works/W4312875989.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1842094663","https://openalex.org/W1987585076","https://openalex.org/W2137802246","https://openalex.org/W2141789294","https://openalex.org/W2194775991","https://openalex.org/W2535838896","https://openalex.org/W2541884796","https://openalex.org/W2547352193","https://openalex.org/W2552857149","https://openalex.org/W2571425027","https://openalex.org/W2618494520","https://openalex.org/W2769644379","https://openalex.org/W2795783309","https://openalex.org/W2802739963","https://openalex.org/W2803867449","https://openalex.org/W2804078603","https://openalex.org/W2885549115","https://openalex.org/W2890924858","https://openalex.org/W2900120080","https://openalex.org/W2904190483","https://openalex.org/W2912592113","https://openalex.org/W2913570153","https://openalex.org/W2914328083","https://openalex.org/W2941142392","https://openalex.org/W2946198813","https://openalex.org/W2946815927","https://openalex.org/W2955213239","https://openalex.org/W2963992805","https://openalex.org/W2978110818","https://openalex.org/W2995022099","https://openalex.org/W3006555759","https://openalex.org/W3008187686","https://openalex.org/W3035449881","https://openalex.org/W3038426846","https://openalex.org/W3046178819","https://openalex.org/W3089426191","https://openalex.org/W3111179237","https://openalex.org/W3119652720","https://openalex.org/W3126083338","https://openalex.org/W3136022984","https://openalex.org/W3168353230","https://openalex.org/W3172547163","https://openalex.org/W3178336997","https://openalex.org/W6736413256"],"related_works":["https://openalex.org/W4400728495","https://openalex.org/W4382203073","https://openalex.org/W4386246415","https://openalex.org/W4415796116","https://openalex.org/W4388818404","https://openalex.org/W4408556794","https://openalex.org/W7211866104","https://openalex.org/W4386245250","https://openalex.org/W3046178819","https://openalex.org/W4214536145"],"abstract_inverted_index":{"Federated":[0],"learning":[1,43],"systems":[2,20,44],"facilitate":[3],"the":[4,37,72,78],"training":[5],"of":[6,12,74,84,95],"global":[7,38,79],"models":[8,39],"across":[9],"large":[10],"numbers":[11],"distributed":[13],"edge-devices":[14],"with":[15,26,50],"potentially":[16],"heterogeneous":[17],"data.":[18],"Such":[19],"operate":[21],"in":[22,92],"resource":[23],"constrained":[24],"settings":[25,96],"intermittent":[27],"client":[28,66],"availability":[29],"and/or":[30],"time-varying":[31],"communication":[32,103],"constraints.":[33],"As":[34],"a":[35,93],"result,":[36],"trained":[40],"by":[41,55],"federated":[42,85,114],"may":[45],"be":[46],"biased":[47],"towards":[48],"clients":[49,100],"higher":[51],"availability.":[52],"We":[53,122],"proposeFederatedAveragingAided":[54],"anAdaptiveSamplingTechnique":[56],"(F3ast),":[57],"an":[58,64],"unbiased":[59],"algorithm":[60,89],"that":[61],"dynamically":[62],"learns":[63],"availability-dependent":[65],"selection":[67],"strategy":[68],"which":[69],"asymptotically":[70],"minimizes":[71],"impact":[73],"client-sampling":[75],"variance":[76],"on":[77,109],"model's":[80],"convergence,":[81],"enhancing":[82],"performance":[83],"learning.":[86],"The":[87],"proposed":[88],"is":[90],"tested":[91],"variety":[94],"for":[97],"intermittently":[98],"available":[99],"operating":[101],"under":[102],"constraints,":[104],"and":[105,112,119,127,132,134,138],"its":[106],"efficacy":[107],"demonstrated":[108],"synthetic":[110],"data":[111],"realistically":[113],"benchmarking":[115],"experiments":[116],"using":[117],"CIFAR100":[118,137],"Shakespeare":[120],"datasets.":[121],"report":[123],"up":[124],"to":[125],"186%":[126],"8%":[128,133],"accuracy":[129],"improvements":[130],"overFedAvg,":[131],"7%":[135],"overFedAdamon":[136],"Shakespeare,":[139],"respectively.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2023-01-05T00:00:00"}