{"id":"https://openalex.org/W4401413565","doi":"https://doi.org/10.1109/jiot.2024.3440959","title":"FedUVeQCS: Universal Vector Quantized Compressive Sensing for Communication-Efficient Federated Learning","display_name":"FedUVeQCS: Universal Vector Quantized Compressive Sensing for Communication-Efficient Federated Learning","publication_year":2024,"publication_date":"2024-08-08","ids":{"openalex":"https://openalex.org/W4401413565","doi":"https://doi.org/10.1109/jiot.2024.3440959"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3440959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3440959","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5015476218","display_name":"Zhengming Liu","orcid":"https://orcid.org/0009-0009-8105-2243"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhengming Liu","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039712178","display_name":"Hui Wang","orcid":"https://orcid.org/0000-0002-2197-2285"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Wang","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072919277","display_name":"Xiaobo Li","orcid":"https://orcid.org/0000-0003-0607-5567"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobo Li","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015476218"],"corresponding_institution_ids":["https://openalex.org/I135237710"],"apc_list":null,"apc_paid":null,"fwci":0.6129,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67566371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"11","issue":"22","first_page":"37045","last_page":"37056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9907000064849854,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7721456289291382},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5114840269088745},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4099239706993103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3390142321586609}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7721456289291382},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5114840269088745},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4099239706993103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3390142321586609}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3440959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3440959","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2468279889","display_name":null,"funder_award_id":"2022-4-063","funder_id":"https://openalex.org/F4320338470","funder_display_name":"Science Research Foundation of Zhejiang Province"},{"id":"https://openalex.org/G6390086118","display_name":null,"funder_award_id":"62171413","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338470","display_name":"Science Research Foundation of Zhejiang Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1996021349","https://openalex.org/W2015418199","https://openalex.org/W2025079166","https://openalex.org/W2031614119","https://openalex.org/W2071284784","https://openalex.org/W2084071523","https://openalex.org/W2104266187","https://openalex.org/W2112796928","https://openalex.org/W2124295105","https://openalex.org/W2129344187","https://openalex.org/W2140856955","https://openalex.org/W2150412388","https://openalex.org/W2160979406","https://openalex.org/W2293423476","https://openalex.org/W2392296046","https://openalex.org/W2596636257","https://openalex.org/W2606891064","https://openalex.org/W2750384547","https://openalex.org/W2972570881","https://openalex.org/W2981587265","https://openalex.org/W2989289980","https://openalex.org/W2999561085","https://openalex.org/W3033664100","https://openalex.org/W3038426846","https://openalex.org/W3043758338","https://openalex.org/W3101036738","https://openalex.org/W3102449016","https://openalex.org/W3153347425","https://openalex.org/W3182125009","https://openalex.org/W3188554269","https://openalex.org/W3192880923","https://openalex.org/W3203789000","https://openalex.org/W3209696639","https://openalex.org/W3217610115","https://openalex.org/W4210960727","https://openalex.org/W4250955649","https://openalex.org/W4254197176","https://openalex.org/W4285502645","https://openalex.org/W4313627870","https://openalex.org/W4320005491","https://openalex.org/W4323256870","https://openalex.org/W4381620519","https://openalex.org/W4383171443","https://openalex.org/W6728757088","https://openalex.org/W6743688258","https://openalex.org/W6745723224","https://openalex.org/W6746200960","https://openalex.org/W6748019269","https://openalex.org/W6754416507","https://openalex.org/W6757643485","https://openalex.org/W6767676916","https://openalex.org/W6768511045","https://openalex.org/W6799650887"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2390279801","https://openalex.org/W2378166785"],"abstract_inverted_index":{"Traditional":[0],"machine":[1],"learning":[2,25],"involves":[3],"collecting":[4],"data":[5,13,31,159],"from":[6,60],"clients":[7],"to":[8,40,123,200],"a":[9,28,37,87,143],"central":[10],"server,":[11],"where":[12],"may":[14],"not":[15],"be":[16,140],"willingly":[17],"shared":[18],"by":[19,135],"the":[20,56,116,121,125,128,180,190],"clients.":[21],"In":[22,82],"contrast,":[23],"federated":[24],"(FL)":[26],"trains":[27],"model":[29,39,118],"without":[30,120],"sharing.":[32],"The":[33,131],"parameter":[34],"server":[35],"sends":[36],"global":[38],"all":[41],"clients,":[42],"who":[43],"train":[44],"it":[45,163],"locally":[46],"and":[47,80,113,157,161,175],"send":[48],"local":[49,62,117],"updates":[50,119],"back.":[51],"A":[52],"major":[53],"challenge":[54],"is":[55],"high":[57],"communication":[58,67],"overhead":[59],"numerous":[61],"updates.":[63],"To":[64],"address":[65],"this":[66,83],"overhead,":[68],"several":[69],"algorithms":[70,186],"have":[71],"been":[72],"proposed":[73],"for":[74,95,172],"FL":[75,97,109],"tasks,":[76],"such":[77],"as":[78,142],"sparsification":[79],"quantization.":[81],"article,":[84],"we":[85],"propose":[86],"method":[88],"called":[89],"universal":[90,103,136,169],"vector":[91,104,137,170],"quantized":[92,105],"compressive":[93,106],"sensing":[94,107],"communication-efficient":[96],"(FedUVeQCS).":[98],"We":[99,148],"demonstrate":[100],"that":[101],"combining":[102],"with":[108,164],"enables":[110],"dimensionality":[111],"reduction":[112],"quantization":[114,132,138,171],"of":[115,127,182,189,192],"need":[122],"consider":[124],"distribution":[126],"reduced":[129],"data.":[130],"distortion":[133],"caused":[134],"can":[139],"considered":[141],"negligible":[144],"additive":[145],"noise":[146],"term.":[147],"evaluate":[149],"FedUVeQCS":[150,183],"on":[151],"image":[152],"classification":[153],"tasks":[154],"using":[155],"MNIST":[156],"fashion-MNIST":[158],"sets":[160],"compare":[162],"baseline":[165,185],"algorithms,":[166],"including":[167],"FedAvg,":[168],"FL,":[173],"Top-k,":[174],"FedPAQ.":[176],"Numerical":[177],"results":[178],"show":[179],"superiority":[181],"over":[184],"in":[187],"terms":[188],"number":[191],"bits":[193],"uploaded":[194],"while":[195],"maintaining":[196],"testing":[197],"accuracy":[198],"comparable":[199],"FedAvg.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}