{"id":"https://openalex.org/W4289655089","doi":"https://doi.org/10.1109/isit50566.2022.9834609","title":"Optimizing Federated Averaging over Fading Channels","display_name":"Optimizing Federated Averaging over Fading Channels","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289655089","doi":"https://doi.org/10.1109/isit50566.2022.9834609"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834609","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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/A5052825683","display_name":"Yujia Mu","orcid":"https://orcid.org/0009-0006-0364-6706"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yujia Mu","raw_affiliation_strings":["University of Virginia,Department of Electrical and Computer Engineering,USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia,Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016749653","display_name":"Cong Shen","orcid":"https://orcid.org/0000-0002-3148-4453"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cong Shen","raw_affiliation_strings":["University of Virginia,Department of Electrical and Computer Engineering,USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia,Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I51556381"]}]},{"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,Department of Electrical Engineering,Israel"],"affiliations":[{"raw_affiliation_string":"Weizmann Institute of Science,Department of Electrical Engineering,Israel","institution_ids":["https://openalex.org/I53964585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052825683"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":0.2078,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.40002155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1277","last_page":"1281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9948999881744385,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9944000244140625,"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/fading","display_name":"Fading","score":0.9614413976669312},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6988013982772827},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.6882818341255188},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.6716578006744385},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6227493286132812},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5874453186988831},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5646600127220154},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5094829201698303},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4591519236564636},{"id":"https://openalex.org/keywords/fading-distribution","display_name":"Fading distribution","score":0.4228998124599457},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3806310296058655},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3367588520050049},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2364451289176941},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22898554801940918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21322229504585266},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12411603331565857},{"id":"https://openalex.org/keywords/rayleigh-fading","display_name":"Rayleigh fading","score":0.05936339497566223}],"concepts":[{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.9614413976669312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6988013982772827},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.6882818341255188},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.6716578006744385},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6227493286132812},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5874453186988831},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5646600127220154},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5094829201698303},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4591519236564636},{"id":"https://openalex.org/C161126049","wikidata":"https://www.wikidata.org/wiki/Q5429266","display_name":"Fading distribution","level":5,"score":0.4228998124599457},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3806310296058655},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3367588520050049},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2364451289176941},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22898554801940918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21322229504585266},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12411603331565857},{"id":"https://openalex.org/C56985126","wikidata":"https://www.wikidata.org/wiki/Q854039","display_name":"Rayleigh fading","level":4,"score":0.05936339497566223},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834609","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":26,"referenced_works":["https://openalex.org/W595252221","https://openalex.org/W1806891645","https://openalex.org/W1815076433","https://openalex.org/W1997834106","https://openalex.org/W2912592113","https://openalex.org/W2963179579","https://openalex.org/W2981138228","https://openalex.org/W2999074226","https://openalex.org/W3006919779","https://openalex.org/W3088234149","https://openalex.org/W3108383389","https://openalex.org/W3117560501","https://openalex.org/W3118608800","https://openalex.org/W3170610580","https://openalex.org/W3196101383","https://openalex.org/W3212066104","https://openalex.org/W4250589301","https://openalex.org/W4318619660","https://openalex.org/W6638545294","https://openalex.org/W6728757088","https://openalex.org/W6752191696","https://openalex.org/W6754143808","https://openalex.org/W6758757267","https://openalex.org/W6782318606","https://openalex.org/W6787942926","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2372177549","https://openalex.org/W4289713079","https://openalex.org/W2354812485","https://openalex.org/W2157247765","https://openalex.org/W1533563241","https://openalex.org/W2375094708","https://openalex.org/W1975074522","https://openalex.org/W1541825612","https://openalex.org/W2427030663","https://openalex.org/W4289655089"],"abstract_inverted_index":{"Deep":[0],"fading":[1,16,44,110,148],"represents":[2],"the":[3,29,47,64,83,89,102,119,137],"typical":[4],"error":[5],"event":[6],"when":[7,42],"communicating":[8],"over":[9,24,109],"wireless":[10,25],"channels.":[11],"We":[12,153],"show":[13],"that":[14,123],"deep":[15,43],"is":[17,56,93,133],"particularly":[18],"detrimental":[19],"for":[20,39,118,142],"federated":[21],"learning":[22,79,151],"(FL)":[23],"communications.":[26],"In":[27],"particular,":[28],"celebrated":[30],"FEDAVG":[31],"and":[32,112,135,149],"several":[33,158],"of":[34,53],"its":[35],"variants":[36],"break":[37],"down":[38],"FL":[40,160],"tasks":[41],"exists":[45],"in":[46],"communication":[48],"phase.":[49],"The":[50,128],"main":[51],"contribution":[52],"this":[54,125],"paper":[55],"an":[57,98,115],"optimal":[58,130],"global":[59],"model":[60],"aggregation":[61,121,131],"method":[62],"at":[63,88],"parameter":[65],"server,":[66],"which":[67],"allocates":[68],"different":[69,72],"weights":[70,122],"to":[71],"clients":[73],"based":[74],"on":[75,101],"not":[76],"only":[77],"their":[78],"characteristics":[80],"but":[81],"also":[82],"instantaneous":[84],"channel":[85],"state":[86],"information":[87],"receiver":[90],"(CSIR).":[91],"This":[92],"accomplished":[94],"by":[95],"first":[96],"deriving":[97],"upper":[99,126],"bound":[100],"parallel":[103],"stochastic":[104],"gradient":[105],"descent":[106],"(SGD)":[107],"convergence":[108,140],"channels,":[111],"then":[113],"solving":[114],"optimization":[116],"problem":[117],"server":[120],"minimizes":[124],"bound.":[127],"derived":[129],"solution":[132],"closed-form,":[134],"achieves":[136],"well-known":[138],"O(1/t)":[139],"rate":[141],"strongly-convex":[143],"loss":[144],"functions":[145],"under":[146],"arbitrary":[147],"decaying":[150],"rates.":[152],"validate":[154],"our":[155],"approach":[156],"using":[157],"real-world":[159],"tasks.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}