{"id":"https://openalex.org/W4408324905","doi":"https://doi.org/10.1109/globecom52923.2024.10901238","title":"FedDAFL: Federated Transfer Learning with Domain Adaptation for Frugally Labeled Datasets","display_name":"FedDAFL: Federated Transfer Learning with Domain Adaptation for Frugally Labeled Datasets","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4408324905","doi":"https://doi.org/10.1109/globecom52923.2024.10901238"},"language":"en","primary_location":{"id":"doi:10.1109/globecom52923.2024.10901238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","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/A5019579175","display_name":"Ferdinand Kahenga","orcid":null},"institutions":[{"id":"https://openalex.org/I869660684","display_name":"University of the Western Cape","ror":"https://ror.org/00h2vm590","country_code":"ZA","type":"education","lineage":["https://openalex.org/I869660684"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Ferdinand Kahenga","raw_affiliation_strings":["University of the Western Cape,Department of Computer Science,Cape Town,South Africa"],"affiliations":[{"raw_affiliation_string":"University of the Western Cape,Department of Computer Science,Cape Town,South Africa","institution_ids":["https://openalex.org/I869660684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063116320","display_name":"Antoine Bagula","orcid":"https://orcid.org/0000-0003-0774-5251"},"institutions":[{"id":"https://openalex.org/I869660684","display_name":"University of the Western Cape","ror":"https://ror.org/00h2vm590","country_code":"ZA","type":"education","lineage":["https://openalex.org/I869660684"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Antoine Bagula","raw_affiliation_strings":["University of the Western Cape,Department of Computer Science,Cape Town,South Africa"],"affiliations":[{"raw_affiliation_string":"University of the Western Cape,Department of Computer Science,Cape Town,South Africa","institution_ids":["https://openalex.org/I869660684"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050881965","display_name":"Sajal K. Das","orcid":"https://orcid.org/0000-0002-9471-0868"},"institutions":[{"id":"https://openalex.org/I869660684","display_name":"University of the Western Cape","ror":"https://ror.org/00h2vm590","country_code":"ZA","type":"education","lineage":["https://openalex.org/I869660684"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Sajal K. Das","raw_affiliation_strings":["University of the Western Cape,Department of Computer Science,Cape Town,South Africa"],"affiliations":[{"raw_affiliation_string":"University of the Western Cape,Department of Computer Science,Cape Town,South Africa","institution_ids":["https://openalex.org/I869660684"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019579175"],"corresponding_institution_ids":["https://openalex.org/I869660684"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25984557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2142","last_page":"2147"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9872000217437744,"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":0.9872000217437744,"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/domain-adaptation","display_name":"Domain adaptation","score":0.8854562640190125},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.8060156106948853},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7880939841270447},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.759769082069397},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6078095436096191},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33959704637527466}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.8854562640190125},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.8060156106948853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7880939841270447},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.759769082069397},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6078095436096191},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33959704637527466},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"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/globecom52923.2024.10901238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2395579298","https://openalex.org/W2763323349","https://openalex.org/W2964126011","https://openalex.org/W2981720610","https://openalex.org/W3018464563","https://openalex.org/W3162983435","https://openalex.org/W4213177592","https://openalex.org/W4226375232","https://openalex.org/W4311847607","https://openalex.org/W4315778252","https://openalex.org/W6678975374","https://openalex.org/W6687400500","https://openalex.org/W6728757088","https://openalex.org/W6759238902","https://openalex.org/W6770046221","https://openalex.org/W6773005947","https://openalex.org/W6781175393","https://openalex.org/W6781318954","https://openalex.org/W6810756407","https://openalex.org/W6852031748"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W3203792196","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W2955455867","https://openalex.org/W4295929828","https://openalex.org/W3156096827"],"abstract_inverted_index":{"While":[0],"Federated":[1,91,97],"Learning":[2],"(FL)":[3],"manages":[4],"well":[5],"data":[6],"diversity":[7],"in":[8,15,128,148],"distrusted":[9],"learning,":[10,131],"it":[11],"faces":[12],"additional":[13],"complexities":[14],"scenarios":[16],"with":[17,48,87],"\"frugal":[18],"labeling,\"":[19],"where":[20],"the":[21,67,116],"client":[22],"nodes":[23],"host":[24],"a":[25,37,62],"mix":[26],"of":[27,69],"partially":[28],"or":[29,109],"fully":[30,53],"unlabelled":[31,49,83],"datasets.":[32,113],"This":[33],"paper":[34],"introduces":[35],"FedDAFL,":[36],"novel":[38],"approach":[39],"tailored":[40],"for":[41],"label-scarce":[42],"federated":[43,129],"settings,":[44],"that":[45],"enables":[46],"learners":[47],"datasets":[50,144],"to":[51,76,158],"leverage":[52],"labelled":[54],"teachers,":[55],"thus":[56],"incorporating":[57],"domain":[58],"adaptation":[59],"techniques":[60,89],"within":[61],"multi-teacher":[63],"multi-learner":[64],"framework.":[65],"Through":[66],"integration":[68],"self-learning":[70],"and":[71,96,107,152],"semi-supervised":[72],"methods,":[73],"FedDAFL":[74,122],"aims":[75],"enhance":[77],"model":[78],"accuracy":[79,104],"using":[80],"each":[81],"client\u2019s":[82],"data.":[84],"Comparative":[85],"analysis":[86],"established":[88],"like":[90],"Adversarial":[92],"Domain":[93],"Adaptation":[94],"(FADA)":[95],"Knowledge":[98],"Alignment":[99],"(FedKA),":[100],"demonstrates":[101],"FedDAFL\u2019s":[102,146],"superior":[103],"across":[105],"independent":[106],"identically":[108],"non-identically":[110],"distributed":[111],"(non-IID)":[112],"Even":[114],"if":[115],"clients":[117],"possess":[118],"single":[119],"class":[120],"data,":[121],"adeptly":[123],"tackles":[124],"frugal":[125],"labeling":[126],"challenges":[127],"transfer":[130],"exhibiting":[132],"competitive":[133],"performance":[134],"against":[135],"existing":[136],"methods.":[137],"Results":[138],"validated":[139],"on":[140],"Pneumonia":[141],"chest":[142],"X-ray":[143],"underscore":[145],"adaptability":[147],"handling":[149],"limited":[150],"labels":[151],"non-IID":[153],"setups,":[154],"demonstrating":[155],"its":[156],"applications":[157],"various":[159],"settings.":[160]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}