{"id":"https://openalex.org/W4412722227","doi":"https://doi.org/10.1109/tnnls.2025.3586600","title":"Decoupling Neural Networks to Leverage Uniform Representation and Balance Personalization and Collaboration in Federated Learning","display_name":"Decoupling Neural Networks to Leverage Uniform Representation and Balance Personalization and Collaboration in Federated Learning","publication_year":2025,"publication_date":"2025-07-29","ids":{"openalex":"https://openalex.org/W4412722227","doi":"https://doi.org/10.1109/tnnls.2025.3586600","pmid":"https://pubmed.ncbi.nlm.nih.gov/40729707"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3586600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3586600","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5015951666","display_name":"Zhangmin Huang","orcid":"https://orcid.org/0000-0001-9294-4196"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhangmin Huang","raw_affiliation_strings":["Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441285","display_name":"Pengcheng Wang","orcid":"https://orcid.org/0000-0002-3539-8376"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Wang","raw_affiliation_strings":["Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050393292","display_name":"Shaojie Tang","orcid":"https://orcid.org/0000-0001-9261-5210"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaojie Tang","raw_affiliation_strings":["Department of Management Science and Systems, School of Management, Center for AI Business Innovation, University at Buffalo, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Management Science and Systems, School of Management, Center for AI Business Innovation, University at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081670721","display_name":"Bo Lyu","orcid":"https://orcid.org/0000-0003-1595-8361"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Lyu","raw_affiliation_strings":["Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036840192","display_name":"Lingfang Zeng","orcid":"https://orcid.org/0000-0003-3130-3015"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingfang Zeng","raw_affiliation_strings":["Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5015951666"],"corresponding_institution_ids":["https://openalex.org/I4210123185"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10126871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"10","first_page":"18642","last_page":"18652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9980999827384949,"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":0.9980999827384949,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9695000052452087,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9228000044822693,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7273882627487183},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6554337739944458},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6197580695152283},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5821424126625061},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.5617027282714844},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5458805561065674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49794769287109375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4415869414806366},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4130021929740906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7273882627487183},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6554337739944458},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6197580695152283},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5821424126625061},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5617027282714844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5458805561065674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49794769287109375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4415869414806366},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4130021929740906},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3586600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3586600","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40729707","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40729707","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1440843720","display_name":null,"funder_award_id":"LQ24F020029","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6435396388","display_name":null,"funder_award_id":"2022YFB4500405","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2131953535","https://openalex.org/W2194775991","https://openalex.org/W2965862774","https://openalex.org/W2995022099","https://openalex.org/W3006752097","https://openalex.org/W3080934299","https://openalex.org/W4233428539","https://openalex.org/W4249057613","https://openalex.org/W4283796083","https://openalex.org/W4287332481","https://openalex.org/W4377713808","https://openalex.org/W4383468656","https://openalex.org/W4390872538","https://openalex.org/W4390873050","https://openalex.org/W4402754306"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Federated":[0],"learning":[1,5],"(FL),":[2],"a":[3,58,63,73],"distributed":[4],"paradigm":[6],"focused":[7],"on":[8,148],"preserving":[9],"data":[10,17,27],"privacy,":[11],"faces":[12],"challenges":[13],"due":[14],"to":[15,76,97,116],"varying":[16],"distributions":[18],"among":[19],"clients,":[20],"impacting":[21],"global":[22,81],"model":[23],"performance.":[24],"To":[25],"mitigate":[26],"heterogeneity,":[28],"we":[29,131],"propose":[30],"FedUB-a":[31],"personalized":[32,105,113],"FL":[33],"framework":[34],"leveraging":[35],"uniform":[36,49],"feature":[37,60],"representation":[38,50,65],"and":[39,42,62,82,107,156],"balancing":[40],"personalization":[41],"collaboration":[43],"in":[44,52,92,141],"the":[45,48,78,90,93,99,104,108,112,120,124,133,136,143,153],"classifier.":[46],"Specifically,":[47,111],"(UR)":[51],"FedUB":[53],"provides":[54],"all":[55],"clients":[56],"with":[57],"shared":[59],"extractor":[61],"common":[64],"centroid":[66],"(RC).":[67],"Achieving":[68],"this":[69],"uniformity":[70],"involves":[71],"incorporating":[72],"regularization":[74],"term":[75],"reduce":[77],"gap":[79],"between":[80],"local":[83,117,128],"RCs.":[84],"Additionally,":[85],"an":[86],"importance":[87],"estimation":[88],"of":[89,135,160],"parameters":[91,100],"classifier":[94,125],"is":[95],"provided":[96],"partition":[98],"into":[101],"two":[102],"parts:":[103],"component":[106,114,122],"collaborated":[109,121],"component.":[110],"adapts":[115],"data,":[118],"while":[119],"prevents":[123],"from":[126],"overfitting":[127],"data.":[129],"Theoretically,":[130],"establish":[132],"existence":[134],"UR,":[137],"demonstrating":[138],"its":[139],"effectiveness":[140],"reducing":[142],"average":[144],"generalization":[145,158],"bound.":[146],"Experiments":[147],"benchmark":[149],"datasets":[150],"consistently":[151],"demonstrate":[152],"performance":[154],"gains":[155],"improved":[157],"behavior":[159],"FedUB.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
