{"id":"https://openalex.org/W4389544595","doi":"https://doi.org/10.1109/vtc2023-fall60731.2023.10333645","title":"Deep Learning Based Coded Over-the-Air Computation for Personalized Federated Learning","display_name":"Deep Learning Based Coded Over-the-Air Computation for Personalized Federated Learning","publication_year":2023,"publication_date":"2023-10-10","ids":{"openalex":"https://openalex.org/W4389544595","doi":"https://doi.org/10.1109/vtc2023-fall60731.2023.10333645"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2023-fall60731.2023.10333645","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vtc2023-fall60731.2023.10333645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5112982229","display_name":"Danni Chen","orcid":"https://orcid.org/0009-0004-5040-9303"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danni Chen","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101490867","display_name":"Ming Lei","orcid":"https://orcid.org/0000-0002-8740-1434"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Lei","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ming-Min Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Min Zhao","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340373","display_name":"An Liu","orcid":"https://orcid.org/0000-0002-6368-576X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An Liu","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113067924","display_name":"Sikai Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sikai Sheng","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China,310027","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Hangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9977999925613403,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9947999715805054,"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":0.7966916561126709},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6289461851119995},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.5820006728172302},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5807287096977234},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5740028023719788},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5635360479354858},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4937339723110199},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4699547290802002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46775054931640625},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.46226441860198975},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.45328548550605774},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4294324219226837},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35287269949913025},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.35122543573379517},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2679409980773926}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7966916561126709},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6289461851119995},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.5820006728172302},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5807287096977234},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5740028023719788},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5635360479354858},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4937339723110199},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4699547290802002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46775054931640625},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.46226441860198975},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.45328548550605774},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4294324219226837},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35287269949913025},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.35122543573379517},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2679409980773926},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","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},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2023-fall60731.2023.10333645","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vtc2023-fall60731.2023.10333645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2005196269","https://openalex.org/W2564810971","https://openalex.org/W2616316705","https://openalex.org/W2624989916","https://openalex.org/W2907379776","https://openalex.org/W2981138228","https://openalex.org/W2991236681","https://openalex.org/W3028318515","https://openalex.org/W3099314130","https://openalex.org/W3112044954","https://openalex.org/W3193853809","https://openalex.org/W3213161637","https://openalex.org/W6779174293","https://openalex.org/W6784336702"],"related_works":["https://openalex.org/W4317941881","https://openalex.org/W4323521275","https://openalex.org/W2998530156","https://openalex.org/W4322761281","https://openalex.org/W3035996294","https://openalex.org/W4238233472","https://openalex.org/W2954034773","https://openalex.org/W3013510494","https://openalex.org/W4385893187","https://openalex.org/W4320067866"],"abstract_inverted_index":{"Federated":[0],"learning":[1,6],"(FL)":[2],"is":[3,104,166],"an":[4],"edge":[5,30,45],"framework":[7,73,165],"that":[8,141,161],"has":[9,19],"received":[10],"significant":[11],"attention":[12],"recently.":[13],"However,":[14],"the":[15,27,34,59,108,117,123,151,155,162,171],"cost":[16],"of":[17,29,36,64,125,173],"communication":[18],"become":[20],"a":[21,69,87,98,137],"major":[22],"challenge":[23],"for":[24,93],"FL":[25,72,178],"as":[26],"number":[28],"devices":[31,46],"grows":[32],"and":[33,51,61,154],"complexity":[35],"training":[37],"models":[38,144],"increases.":[39],"Besides,":[40,97],"data":[41],"samples":[42,127],"across":[43],"all":[44],"are":[47],"usually":[48],"not":[49,114],"independent":[50],"identically":[52],"distributed":[53],"(non-IID),":[54],"posing":[55],"additional":[56],"challenges":[57],"to":[58,145,168],"convergence":[60],"model":[62,153],"accuracy":[63],"FL.":[65],"Therefore,":[66],"we":[67,85,135],"propose":[68,136],"novel":[70],"personalized":[71,138,148],"based":[74,106],"on":[75,107],"deep":[76,88],"coded":[77],"over-the-air":[78],"computation,":[79],"named":[80],"DipFL.":[81],"In":[82,133],"this":[83],"framework,":[84],"design":[86],"AirComp":[89],"aggregation":[90],"(DACA)":[91],"module":[92,103,140],"n-to-1":[94],"information":[95],"aggregation.":[96],"joint":[99],"source-channel":[100],"coding":[101],"(JSCC)":[102],"designed":[105],"variational":[109],"auto-encoder":[110],"(VAE)":[111],"model,":[112],"which":[113],"only":[115],"encodes":[116],"transmitted":[118,174],"data,":[119,175],"but":[120],"also":[121],"reduces":[122],"bias":[124],"local":[126,143,156],"by":[128,149],"introducing":[129],"certain":[130],"regularisation":[131],"terms.":[132],"addition,":[134],"mix":[139],"allows":[142],"be":[146],"more":[147],"mixing":[150],"global":[152],"models.":[157],"Simulation":[158],"results":[159],"confirm":[160],"proposed":[163],"DipFL":[164],"able":[167],"significantly":[169],"reduce":[170],"amount":[172],"while":[176],"improving":[177],"performance":[179],"especially":[180],"at":[181],"low":[182],"signal-to-noise":[183],"regimes.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
