{"id":"https://openalex.org/W4414538859","doi":"https://doi.org/10.1109/icc52391.2025.11161049","title":"FedMKD: Personalized Federated Learning with Memory Knowledge Distillation","display_name":"FedMKD: Personalized Federated Learning with Memory Knowledge Distillation","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414538859","doi":"https://doi.org/10.1109/icc52391.2025.11161049"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5109571184","display_name":"Tien-Chih Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianjia Lin","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University,Fuzhou,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049937294","display_name":"Zhou Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou Tan","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University,Fuzhou,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058120371","display_name":"Ximeng Liu","orcid":"https://orcid.org/0000-0002-4238-3295"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ximeng Liu","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University,Fuzhou,China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109571184"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15401552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4945","last_page":"4950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.994700014591217,"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":0.994700014591217,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9081000089645386,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11161049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2163922914","https://openalex.org/W2407386500","https://openalex.org/W2995022099","https://openalex.org/W3096572172","https://openalex.org/W3112044954","https://openalex.org/W3200318570","https://openalex.org/W4281557629","https://openalex.org/W4285601288","https://openalex.org/W4285737960","https://openalex.org/W4382463479"],"related_works":[],"abstract_inverted_index":{"In":[0,22,42],"recent":[1],"years,":[2],"privacy":[3,17],"concerns":[4],"have":[5],"been":[6],"receiving":[7],"increasing":[8],"attention.":[9],"Federated":[10],"learning":[11,67],"(FL)":[12],"has":[13],"emerged":[14],"to":[15,88,111,146,154],"address":[16,59],"challenges":[18],"in":[19,138,150],"machine":[20],"learning.":[21],"this":[23,60],"framework,":[24],"a":[25,31,44,64,147],"group":[26],"of":[27,39,50,75,92,105,134],"clients":[28,34],"collaborates":[29],"with":[30],"server,":[32],"where":[33],"upload":[35],"model":[36,94],"parameters":[37,95],"instead":[38],"raw":[40],"data.":[41],"FL,":[43],"key":[45],"challenge":[46],"is":[47],"the":[48,73,76,90,98,103,106,113,124,132],"presence":[49],"non-independent":[51],"and":[52,85,108],"identically":[53],"distributed":[54],"data":[55],"among":[56],"clients.":[57],"To":[58],"issue,":[61],"we":[62],"propose":[63],"personalized":[65],"federated":[66],"algorithm":[68,81,137],"(FedMKD)":[69],"that":[70],"fully":[71],"considers":[72],"characteristics":[74],"previous":[77],"round's":[78],"model.":[79,115],"Our":[80],"leverages":[82],"knowledge":[83],"distillation":[84],"gradient":[86],"descent":[87],"optimize":[89],"proportion":[91],"global":[93,107],"used":[96],"during":[97,121],"initialization":[99],"process.":[100],"FedMKD":[101,143],"combines":[102],"strengths":[104],"memory":[109],"models":[110],"initialize":[112],"local":[114,125],"It":[116],"effectively":[117],"retains":[118],"historical":[119],"information":[120],"training,":[122],"enhancing":[123],"model's":[126],"performance.":[127],"Extensive":[128],"experimental":[129],"results":[130],"demonstrate":[131],"effectiveness":[133],"our":[135],"proposed":[136],"addressing":[139],"statistical":[140],"heterogeneity":[141],"issues.":[142],"achieves":[144],"up":[145],"10.66%":[148],"improvement":[149],"test":[151],"accuracy":[152],"compared":[153],"eight":[155],"state-of-the-art":[156],"baselines.":[157]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}