{"id":"https://openalex.org/W4372267131","doi":"https://doi.org/10.1109/icassp49357.2023.10096678","title":"Boosting Semi-Supervised Federated Learning with Model Personalization and Client-Variance-Reduction","display_name":"Boosting Semi-Supervised Federated Learning with Model Personalization and Client-Variance-Reduction","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372267131","doi":"https://doi.org/10.1109/icassp49357.2023.10096678"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100328224","display_name":"Shuai Wang","orcid":"https://orcid.org/0000-0001-6457-9478"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Shuai Wang","raw_affiliation_strings":["Singapore University of Technology and Design,Singapore,487372"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design,Singapore,487372","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102815432","display_name":"Yanqing Xu","orcid":"https://orcid.org/0000-0002-1503-2983"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqing Xu","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen,China,518172"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen,China,518172","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101942697","display_name":"Yanli Yuan","orcid":"https://orcid.org/0000-0003-4592-5333"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanli Yuan","raw_affiliation_strings":["Beijing Institute of Technology,Beijing,China,100081"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,Beijing,China,100081","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114778174","display_name":"Xiuhua Wang","orcid":"https://orcid.org/0000-0002-9223-8328"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuhua Wang","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China,430074"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China,430074","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030858163","display_name":"Tony Q. S. Quek","orcid":"https://orcid.org/0000-0002-4037-3149"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Tony Q. S. Quek","raw_affiliation_strings":["Singapore University of Technology and Design,Singapore,487372"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design,Singapore,487372","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100328224"],"corresponding_institution_ids":["https://openalex.org/I152815399"],"apc_list":null,"apc_paid":null,"fwci":0.3497,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63057294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9690999984741211,"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/computer-science","display_name":"Computer science","score":0.7983616590499878},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7213099002838135},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.687157392501831},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6837154626846313},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.5910731554031372},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.5784144401550293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5775891542434692},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5756641626358032},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5472232699394226},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.5033852458000183},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49514785408973694},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4757675528526306},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4512060880661011},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4128257930278778},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32492515444755554},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09969919919967651}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7983616590499878},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7213099002838135},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.687157392501831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6837154626846313},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5910731554031372},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.5784144401550293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5775891542434692},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5756641626358032},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5472232699394226},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.5033852458000183},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49514785408973694},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4757675528526306},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4512060880661011},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4128257930278778},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32492515444755554},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09969919919967651},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2116612304","https://openalex.org/W2947861550","https://openalex.org/W2949934631","https://openalex.org/W2955213239","https://openalex.org/W2977517840","https://openalex.org/W2996442797","https://openalex.org/W3006555759","https://openalex.org/W3012968339","https://openalex.org/W3038022836","https://openalex.org/W3043723611","https://openalex.org/W3095829109","https://openalex.org/W3099314130","https://openalex.org/W3118608800","https://openalex.org/W3147359051","https://openalex.org/W3155912831","https://openalex.org/W3159080474","https://openalex.org/W3177095755","https://openalex.org/W3195062561","https://openalex.org/W3196463200","https://openalex.org/W3203503583","https://openalex.org/W3205500251","https://openalex.org/W3210497558","https://openalex.org/W3213815372","https://openalex.org/W3214330255","https://openalex.org/W4212905885","https://openalex.org/W4285762978","https://openalex.org/W4318619660","https://openalex.org/W6728757088","https://openalex.org/W6759238902","https://openalex.org/W6762754822","https://openalex.org/W6762930437","https://openalex.org/W6765541894","https://openalex.org/W6768660345","https://openalex.org/W6772197471","https://openalex.org/W6773817997","https://openalex.org/W6774978782","https://openalex.org/W6779174293","https://openalex.org/W6781318954","https://openalex.org/W6784336702","https://openalex.org/W6787972765","https://openalex.org/W6788603650","https://openalex.org/W6790034021","https://openalex.org/W6800377291","https://openalex.org/W6802864417","https://openalex.org/W6803871889","https://openalex.org/W6808989939"],"related_works":["https://openalex.org/W90906771","https://openalex.org/W2018828772","https://openalex.org/W2529185025","https://openalex.org/W2052708136","https://openalex.org/W2945629716","https://openalex.org/W4283775266","https://openalex.org/W3043533097","https://openalex.org/W4298860769","https://openalex.org/W2767126220","https://openalex.org/W3007770227"],"abstract_inverted_index":{"Recently,":[0],"federated":[1],"learning":[2],"(FL)":[3],"has":[4],"been":[5,36],"increasingly":[6],"appealing":[7],"in":[8],"distributed":[9],"signal":[10],"processing":[11],"and":[12,22,79,87,94,116,125,134],"machine":[13],"learning.":[14],"Nevertheless,":[15],"the":[16,44,48,57,69,74,108,151,156],"practical":[17],"challenges":[18],"of":[19,43,110,121,153],"label":[20],"deficiency":[21],"client":[23,62,132],"heterogeneity":[24,133],"form":[25],"a":[26,85,111,136],"bottleneck":[27],"to":[28,38,131,149],"its":[29],"wide":[30],"adoption.":[31],"Although":[32],"numerous":[33],"efforts":[34],"have":[35],"devoted":[37],"semi-":[39],"supervised":[40],"FL,":[41],"most":[42],"adopted":[45],"algorithms":[46],"follow":[47],"same":[49],"spirit":[50],"as":[51],"FedAvg,":[52],"thus":[53],"heavily":[54],"suffering":[55],"from":[56],"adverse":[58],"effects":[59],"caused":[60],"by":[61,72],"heterogeneity.":[63],"In":[64,81],"this":[65],"paper,":[66],"we":[67,83],"boost":[68],"semi-supervised":[70],"FL":[71],"addressing":[73],"issue":[75],"using":[76],"model":[77,95],"personalization":[78],"client-variance-reduction.":[80],"particular,":[82],"propose":[84,99],"novel":[86,112],"unified":[88],"problem":[89],"formulation":[90],"based":[91],"on":[92,142],"pseudo-labeling":[93],"interpolation.":[96],"We":[97],"then":[98],"an":[100],"effective":[101],"algorithm,":[102],"named":[103],"FedCPSL,":[104],"which":[105],"judiciously":[106],"adopts":[107],"schemes":[109],"momentum-based":[113],"client-":[114],"variance-reduction":[115],"normalized":[117],"averaging.":[118],"Convergence":[119],"property":[120],"FedCPSL":[122,128,154],"is":[123,129],"analyzed":[124],"shows":[126],"that":[127],"resilient":[130],"obtains":[135],"sublinear":[137],"convergence":[138],"rate.":[139],"Experimental":[140],"results":[141],"image":[143],"classification":[144],"tasks":[145],"are":[146],"also":[147],"presented":[148],"demonstrate":[150],"efficacy":[152],"over":[155],"benchmark":[157],"algorithms.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
