{"id":"https://openalex.org/W4312065440","doi":"https://doi.org/10.1007/s11280-022-01119-x","title":"PerHeFed: A general framework of personalized federated learning for heterogeneous convolutional neural networks","display_name":"PerHeFed: A general framework of personalized federated learning for heterogeneous convolutional neural networks","publication_year":2022,"publication_date":"2022-12-12","ids":{"openalex":"https://openalex.org/W4312065440","doi":"https://doi.org/10.1007/s11280-022-01119-x","pmid":"https://pubmed.ncbi.nlm.nih.gov/36531189"},"language":"en","primary_location":{"id":"doi:10.1007/s11280-022-01119-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11280-022-01119-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11280-022-01119-x.pdf","source":{"id":"https://openalex.org/S129236917","display_name":"World Wide Web","issn_l":"1386-145X","issn":["1386-145X","1573-1413"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"World Wide Web","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11280-022-01119-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102481460","display_name":"Le Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I4210130660","display_name":"Xi'an High Tech University","ror":"https://ror.org/03vt7za95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210130660"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Ma","raw_affiliation_strings":["Xi'an Institute of High Technology, Xi'An, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Institute of High Technology, Xi'An, China","institution_ids":["https://openalex.org/I4210130660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034353217","display_name":"Yuying Liao","orcid":"https://orcid.org/0000-0002-0466-3544"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"YuYing Liao","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115604777","display_name":"Bin Zhou","orcid":"https://orcid.org/0000-0002-0950-9298"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zhou","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086424688","display_name":"Wen Xi","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Xi","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5034353217"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.6937,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.75923411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":"4","first_page":"2027","last_page":"2049"},"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":0.9742000102996826,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9641000032424927,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.9187127351760864},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.7209434509277344},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6755070686340332},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5386384129524231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49305006861686707},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.4620906710624695},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4404248595237732},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4378580152988434},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.34297502040863037},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.10916545987129211},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.08751055598258972}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9187127351760864},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7209434509277344},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6755070686340332},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5386384129524231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49305006861686707},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.4620906710624695},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4404248595237732},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4378580152988434},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34297502040863037},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.10916545987129211},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.08751055598258972},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s11280-022-01119-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11280-022-01119-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11280-022-01119-x.pdf","source":{"id":"https://openalex.org/S129236917","display_name":"World Wide Web","issn_l":"1386-145X","issn":["1386-145X","1573-1413"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"World Wide Web","raw_type":"journal-article"},{"id":"pmid:36531189","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36531189","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":"World wide web","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9743105","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9743105","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"World Wide Web","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s11280-022-01119-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11280-022-01119-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11280-022-01119-x.pdf","source":{"id":"https://openalex.org/S129236917","display_name":"World Wide Web","issn_l":"1386-145X","issn":["1386-145X","1573-1413"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"World Wide Web","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2968818819","display_name":null,"funder_award_id":"62172428","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4092121983","display_name":null,"funder_award_id":"2019B010136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6306994556","display_name":null,"funder_award_id":"61732022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7851391746","display_name":null,"funder_award_id":"61732004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312065440.pdf","grobid_xml":"https://content.openalex.org/works/W4312065440.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2535690855","https://openalex.org/W2541884796","https://openalex.org/W2591882872","https://openalex.org/W2805182940","https://openalex.org/W2953257359","https://openalex.org/W2963446712","https://openalex.org/W2963456518","https://openalex.org/W2995022099","https://openalex.org/W3021026170","https://openalex.org/W3089578458","https://openalex.org/W3095251140","https://openalex.org/W3098021089","https://openalex.org/W3112044954","https://openalex.org/W3126765304","https://openalex.org/W3134527412","https://openalex.org/W3167262308","https://openalex.org/W3174842369","https://openalex.org/W3180608480","https://openalex.org/W3185044643","https://openalex.org/W3193706337","https://openalex.org/W3197915999","https://openalex.org/W3210103168","https://openalex.org/W4200580662","https://openalex.org/W6600100092","https://openalex.org/W6601204288","https://openalex.org/W6602512215","https://openalex.org/W6732699761"],"related_works":["https://openalex.org/W4298221930","https://openalex.org/W2777914285","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Abstract":[0],"In":[1,98],"conventional":[2,230],"federated":[3,24,78,214,231],"learning,":[4],"each":[5],"device":[6],"is":[7,132,209],"restricted":[8],"to":[9,85,116,134,159],"train":[10],"a":[11,73,100,105,182,196],"network":[12],"model":[13,56,89,226],"of":[14,23,35,54,68,137,152,175,204],"the":[15,21,27,44,55,83,121,149,160,176,202,210],"same":[16,45],"structure.":[17],"This":[18],"greatly":[19],"hinders":[20],"application":[22],"learning":[25,79,215],"where":[26],"data":[28,167],"and":[29,40,92,104,129,142,190],"devices":[30,84],"are":[31,111],"quite":[32],"heterogeneous":[33,114,138,153,218],"because":[34],"their":[36,87],"different":[37,223],"hardware":[38],"equipment":[39],"communication":[41,62],"networks.":[42],"At":[43],"time,":[46],"existing":[47],"studies":[48],"have":[49],"shown":[50],"that":[51,145],"transmitting":[52],"all":[53],"parameters":[57,179],"not":[58],"only":[59,181],"has":[60],"heavy":[61],"costs,":[63],"but":[64],"also":[65],"increases":[66],"risk":[67],"privacy":[69],"leakage.":[70],"We":[71],"propose":[72],"general":[74,212],"framework":[75,216],"for":[76,113,217],"personalized":[77,107,150,213],"(PerHeFed),":[80],"which":[81],"enables":[82],"design":[86],"local":[88],"structures":[90],"autonomously":[91],"share":[93],"sub-models":[94,115],"without":[95],"structural":[96],"restrictions.":[97],"PerHeFed,":[99],"simple-but-effective":[101],"mapping":[102],"relation":[103],"novel":[106],"sub-model":[108,178],"aggregation":[109],"method":[110,162,170],"proposed":[112],"be":[117],"aggregated.":[118],"By":[119],"dividing":[120],"aggregations":[122],"into":[123],"two":[124],"primitive":[125],"types":[126],"(i.e.,":[127],"inter-layer":[128],"intra-layer),":[130],"PerHeFed":[131,193],"applicable":[133],"any":[135],"combination":[136],"convolutional":[139,219],"neural":[140],"networks,":[141,220,224],"we":[143],"believe":[144],"this":[146],"can":[147],"satisfy":[148],"requirements":[151],"models.":[154],"Experiments":[155],"show":[156],"that,":[157],"compared":[158],"state-of-the-art":[161],"(e.g.,":[163],"FLOP),":[164],"in":[165,185,199,229],"non-IID":[166],"sets":[168],"our":[169,205,207],"compress":[171],"\u2248":[172],"50":[173],"%":[174],"shared":[177],"with":[180],"4.38%":[183],"drop":[184],"accuracy":[186],"on":[187,191],"SVHN":[188],"dataset":[189],"CIFAR-10,":[192],"even":[194,221],"achieves":[195],"0.3%":[197],"improvement":[198],"accuracy.":[200],"To":[201],"best":[203],"knowledge,":[206],"work":[208],"first":[211],"cross":[222],"addressing":[225],"structure":[227],"unity":[228],"learning.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}