{"id":"https://openalex.org/W4308216582","doi":"https://doi.org/10.1109/allerton49937.2022.9929426","title":"CoBAAF: Controlled Bayesian Air Aggregation Federated Learning from Heterogeneous Data","display_name":"CoBAAF: Controlled Bayesian Air Aggregation Federated Learning from Heterogeneous Data","publication_year":2022,"publication_date":"2022-09-27","ids":{"openalex":"https://openalex.org/W4308216582","doi":"https://doi.org/10.1109/allerton49937.2022.9929426"},"language":"en","primary_location":{"id":"doi:10.1109/allerton49937.2022.9929426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton49937.2022.9929426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","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/A5077036467","display_name":"Tomer Gafni","orcid":"https://orcid.org/0000-0002-5906-1428"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Tomer Gafni","raw_affiliation_strings":["School of Electrical and Computer Engineering, Ben-Gurion University of the Negev,Beer-Sheva,Israel","School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Ben-Gurion University of the Negev,Beer-Sheva,Israel","institution_ids":["https://openalex.org/I124227911"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066085947","display_name":"Kobi Cohen","orcid":"https://orcid.org/0000-0003-0532-009X"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Kobi Cohen","raw_affiliation_strings":["School of Electrical and Computer Engineering, Ben-Gurion University of the Negev,Beer-Sheva,Israel","School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Ben-Gurion University of the Negev,Beer-Sheva,Israel","institution_ids":["https://openalex.org/I124227911"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005913897","display_name":"Yonina C. Eldar","orcid":"https://orcid.org/0000-0003-4358-5304"},"institutions":[{"id":"https://openalex.org/I53964585","display_name":"Weizmann Institute of Science","ror":"https://ror.org/0316ej306","country_code":"IL","type":"education","lineage":["https://openalex.org/I53964585"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yonina C. Eldar","raw_affiliation_strings":["Weizmann Institute of Science,Math and CS Faculty,Rehovot,Israel","Math and CS Faculty, Weizmann Institute of Science, Rehovot, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Weizmann Institute of Science,Math and CS Faculty,Rehovot,Israel","institution_ids":["https://openalex.org/I53964585"]},{"raw_affiliation_string":"Math and CS Faculty, Weizmann Institute of Science, Rehovot, Israel","institution_ids":["https://openalex.org/I53964585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2775,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63748266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9941999912261963,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/computer-science","display_name":"Computer science","score":0.8573212027549744},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5911439061164856},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5854738354682922},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.5492397546768188},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5389379262924194},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.5157890319824219},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4617384374141693},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.44953447580337524},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4367660880088806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43534278869628906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40790724754333496},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38070163130760193},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1557227075099945},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14398112893104553}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8573212027549744},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5911439061164856},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5854738354682922},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.5492397546768188},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5389379262924194},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.5157890319824219},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4617384374141693},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.44953447580337524},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4367660880088806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43534278869628906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40790724754333496},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38070163130760193},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1557227075099945},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14398112893104553},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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":1,"locations":[{"id":"doi:10.1109/allerton49937.2022.9929426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton49937.2022.9929426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9200000166893005,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G5755329095","display_name":null,"funder_award_id":"2640/20","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"},{"id":"https://openalex.org/F4320323051","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1602773783","https://openalex.org/W2016309114","https://openalex.org/W2098741260","https://openalex.org/W2107438106","https://openalex.org/W2606891064","https://openalex.org/W2769644379","https://openalex.org/W2907379776","https://openalex.org/W2919115771","https://openalex.org/W2952215077","https://openalex.org/W2955213239","https://openalex.org/W2960833983","https://openalex.org/W2963179579","https://openalex.org/W2963766684","https://openalex.org/W2969343398","https://openalex.org/W2975043678","https://openalex.org/W3006555759","https://openalex.org/W3015901293","https://openalex.org/W3028318515","https://openalex.org/W3036822879","https://openalex.org/W3038022836","https://openalex.org/W3081130510","https://openalex.org/W3088234149","https://openalex.org/W3101036738","https://openalex.org/W3117560501","https://openalex.org/W3148526481","https://openalex.org/W3200113895","https://openalex.org/W3202820162","https://openalex.org/W4285240303","https://openalex.org/W4318619660","https://openalex.org/W6674709963","https://openalex.org/W6676105031","https://openalex.org/W6680196509","https://openalex.org/W6728757088","https://openalex.org/W6746200960","https://openalex.org/W6752191696","https://openalex.org/W6754341472","https://openalex.org/W6759238902","https://openalex.org/W6765541894","https://openalex.org/W6768511045","https://openalex.org/W6773817997","https://openalex.org/W6787942926"],"related_works":["https://openalex.org/W2889222875","https://openalex.org/W2568907318","https://openalex.org/W2379489406","https://openalex.org/W2209962797","https://openalex.org/W2889474515","https://openalex.org/W2427030663","https://openalex.org/W2022634147","https://openalex.org/W2804048135","https://openalex.org/W3120826507","https://openalex.org/W1770813527"],"abstract_inverted_index":{"Federated":[0],"learning":[1,7,193],"(FL)":[2],"is":[3,30],"an":[4],"emerging":[5],"machine":[6,192],"paradigm":[8],"for":[9,189],"training":[10,190],"models":[11],"across":[12],"multiple":[13],"edge":[14],"devices":[15],"holding":[16],"local":[17,100,111],"data":[18,47,123],"sets,":[19],"without":[20],"explicitly":[21],"exchanging":[22],"the":[23,33,40,55,108,137,142,145,151,155,160,184],"data.":[24,65],"A":[25],"major":[26],"challenge":[27],"in":[28,85,96,110,191],"FL":[29],"to":[31,39,59,120,134,159,168,174],"reduce":[32],"bandwidth":[34],"and":[35,58,102,117,147],"energy":[36],"consumption":[37],"due":[38],"repeated":[41],"transmissions":[42],"of":[43,46,52,63,92,144,157,187],"large":[44,50],"volumes":[45],"by":[48,150],"a":[49,71,89,114,131,170],"number":[51],"users":[53,64,119],"over":[54,126,177],"wireless":[56],"channel,":[57],"handle":[60],"statistical":[61,83],"heterogeneity":[62,84],"In":[66],"this":[67],"paper":[68],"we":[69],"present":[70],"novel":[72],"algorithm,":[73],"dubbed":[74],"Controlled":[75],"Bayesian":[76,132],"Air":[77],"Aggregation":[78],"Federated-learning":[79],"(CoBAAF),":[80],"that":[81,175],"handles":[82],"noisy":[86],"networks":[87],"using":[88,113],"joint":[90],"design":[91],"three":[93],"main":[94],"steps":[95],"FL:":[97],"Model":[98],"distribution,":[99],"training,":[101],"global":[103],"aggregation.":[104],"Specifically,":[105],"CoBAAF":[106,158,188],"controls":[107],"drift":[109],"updates":[112],"correction":[115],"term,":[116],"allows":[118],"transmit":[121],"their":[122],"signal":[124],"simultaneously":[125],"MAC.":[127],"Second,":[128],"it":[129],"adopts":[130],"approach":[133],"average":[135],"properly":[136],"channel":[138],"output,":[139],"thus":[140],"mitigating":[141],"effect":[143],"noise":[146],"fading":[148],"induced":[149],"channel.":[152],"We":[153],"analyze":[154],"convergence":[156,171,186],"loss":[161],"minimizing":[162],"model":[163],"theoretically,":[164],"showing":[165],"its":[166],"ability":[167],"achieve":[169],"rate":[172],"similar":[173],"achieved":[176],"error-free":[178],"channels.":[179],"Extensive":[180],"simulation":[181],"results":[182],"demonstrate":[183],"improved":[185],"problems.":[194]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}