{"id":"https://openalex.org/W7124154521","doi":"https://doi.org/10.1109/icpads67057.2025.11323101","title":"Fine-Grained Privacy-Aware Parameter Coaching for Personalized Federated Learning","display_name":"Fine-Grained Privacy-Aware Parameter Coaching for Personalized Federated Learning","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7124154521","doi":"https://doi.org/10.1109/icpads67057.2025.11323101"},"language":null,"primary_location":{"id":"doi:10.1109/icpads67057.2025.11323101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","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/A5036124449","display_name":"Hongpu Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongpu Jiang","raw_affiliation_strings":["School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019230294","display_name":"Jinxin Zuo","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinxin Zuo","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123017013","display_name":"Yueming Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueming Lu","raw_affiliation_strings":["School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042045889","display_name":"Tingsong Lu","orcid":"https://orcid.org/0000-0003-1036-1988"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingsong Lu","raw_affiliation_strings":["School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123006178","display_name":"Long Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Zhang","raw_affiliation_strings":["School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cybersecurity, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9617000222206116,"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":0.9617000222206116,"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/T11045","display_name":"Privacy, Security, and Data Protection","score":0.00419999985024333,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.0031999999191612005,"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":[{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.8360999822616577},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5213000178337097},{"id":"https://openalex.org/keywords/coaching","display_name":"Coaching","score":0.47269999980926514},{"id":"https://openalex.org/keywords/information-sensitivity","display_name":"Information sensitivity","score":0.44620001316070557},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4262000024318695},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3628999888896942},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.35679998993873596}],"concepts":[{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8360999822616577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8184000253677368},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5213000178337097},{"id":"https://openalex.org/C2779363792","wikidata":"https://www.wikidata.org/wiki/Q1104185","display_name":"Coaching","level":2,"score":0.47269999980926514},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.44620001316070557},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.37310001254081726},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.31220000982284546},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3034000098705292},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2782000005245209},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpads67057.2025.11323101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6885204315185547}],"awards":[{"id":"https://openalex.org/G4893536234","display_name":null,"funder_award_id":"62402057","funder_id":"https://openalex.org/F4320333688","funder_display_name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320333688","display_name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W2023901033","https://openalex.org/W2027982384","https://openalex.org/W2051267297","https://openalex.org/W2473418344","https://openalex.org/W2535690855","https://openalex.org/W2948978827","https://openalex.org/W2963963190","https://openalex.org/W2970606380","https://openalex.org/W2995022099","https://openalex.org/W3033511014","https://openalex.org/W3045674654","https://openalex.org/W3133814152","https://openalex.org/W4225670787","https://openalex.org/W4312634912","https://openalex.org/W4390674625","https://openalex.org/W4390871797","https://openalex.org/W4393156753","https://openalex.org/W4393156769"],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,37,57,65,78],"era":[2],"of":[3,60],"big":[4],"data":[5,33,93],"and":[6,19,126,161,169],"IoT,":[7],"personalized":[8,48,111],"federated":[9,69],"learning":[10],"(pFL)":[11],"addresses":[12],"privacy":[13,118,123,160],"challenges":[14],"by":[15],"keeping":[16],"training":[17],"on-device":[18],"transmitting":[20],"only":[21],"parameter":[22],"updates.":[23],"This":[24,132],"approach":[25],"allows":[26],"each":[27],"client":[28,53],"to":[29,40,88,97,142],"incorporate":[30],"their":[31],"unique":[32],"characteristics,":[34],"effectively":[35],"tailoring":[36],"global":[38],"model":[39],"diverse":[41],"user":[42],"needs.":[43],"However,":[44],"as":[45,85,135],"pFL":[46,170],"leverages":[47],"updates":[49],"that":[50,120],"capture":[51],"individual":[52],"experiences,":[54],"it":[55],"faces":[56],"inherent":[58],"risk":[59],"exposing":[61],"sensitive":[62],"information":[63,155],"during":[64],"aggregation":[66],"process.":[67],"Global":[68],"methods":[70],"like":[71],"FedAvg":[72],"further":[73],"exacerbate":[74],"this":[75],"issue":[76],"when":[77],"non-IID":[79],"assumption":[80],"is":[81],"violated":[82],"across":[83,91],"clients,":[84],"they":[86],"struggle":[87],"maintain":[89],"performance":[90],"varied":[92],"distributions,":[94],"often":[95],"leading":[96],"suboptimal":[98],"results.":[99],"To":[100],"tackle":[101],"this,":[102],"we":[103],"propose":[104,115],"fine-grained":[105,137],"Privacy-aware":[106],"Parameter":[107],"Coaching":[108],"method":[109,158],"for":[110],"Federated":[112],"learning(PPCFed).":[113],"We":[114],"a":[116,136],"dynamic":[117],"matrix":[119,133],"quantifies":[121],"layer-wise":[122],"leakage":[124],"risks":[125],"adaptively":[127],"reweights":[128],"inter-client":[129],"knowledge":[130],"transfer.":[131],"acts":[134],"privacy-aware":[138],"controller,":[139],"enabling":[140],"clients":[141],"selectively":[143],"assimilate":[144],"insights":[145],"from":[146],"others":[147],"without":[148],"additional":[149],"overhead":[150],"while":[151],"actively":[152],"suppressing":[153],"high-risk":[154],"flows.":[156],"Our":[157],"balances":[159],"performance,":[162],"showing":[163],"improved":[164],"results":[165],"in":[166],"heterogeneous":[167],"FL":[168],"environments.":[171]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-01-15T00:00:00"}