{"id":"https://openalex.org/W7154502038","doi":"https://doi.org/10.48550/arxiv.2604.12768","title":"Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization","display_name":"Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154502038","doi":"https://doi.org/10.48550/arxiv.2604.12768"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.12768","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12768","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.12768","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133703026","display_name":"Li Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063605100","display_name":"Yan Sun","orcid":"https://orcid.org/0000-0001-5256-9571"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133721557","display_name":"Dacheng Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Dacheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.4397999942302704,"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":0.4397999942302704,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.1843000054359436,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.054499998688697815,"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/initialization","display_name":"Initialization","score":0.9190000295639038},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7077999711036682},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6302000284194946},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5647000074386597},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4602999985218048},{"id":"https://openalex.org/keywords/generalization-error","display_name":"Generalization error","score":0.40689998865127563},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.33649998903274536}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.9190000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7685999870300293},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7077999711036682},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6302000284194946},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5647000074386597},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4602999985218048},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40720000863075256},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.40689998865127563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3986000120639801},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34290000796318054},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2892000079154968},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.12768","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12768","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.12768","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12768","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"is":[3,40,164],"a":[4,15],"distributed":[5],"paradigm":[6],"that":[7,32,161],"coordinates":[8],"massive":[9],"local":[10,20,47,64,104,111,128,169],"clients":[11],"to":[12,58,131,151,167,183,196,222],"collaboratively":[13],"train":[14],"global":[16,119],"model":[17],"via":[18],"stage-wise":[19,209],"training":[21,105,203],"processes":[22],"on":[23],"the":[24,36,43,60,68,94,100,110,117,122,126,142,148,153,175,208,228],"heterogeneous":[25],"dataset.":[26],"Previous":[27],"works":[28],"have":[29],"implicitly":[30],"studied":[31],"FL":[33,88,229],"suffers":[34],"from":[35,116],"``client-drift''":[37],"problem,":[38],"which":[39,91],"caused":[41],"by":[42,113],"inconsistent":[44],"optimum":[45],"across":[46],"clients.":[48],"However,":[49],"till":[50],"now":[51],"it":[52,172],"still":[53],"lacks":[54],"solid":[55],"theoretical":[56],"analysis":[57,145],"explain":[59],"impact":[61,70],"of":[62,71,102,125],"this":[63,81,168],"inconsistency.":[65],"To":[66],"alleviate":[67],"negative":[69],"``client":[72],"drift''":[73],"and":[74,146],"explore":[75],"its":[76,185],"substance":[77],"in":[78,80,138,156,227],"FL,":[79,139],"paper,":[82],"we":[83,140],"first":[84],"propose":[85],"an":[86],"efficient":[87],"algorithm":[89],"FedInit,":[90],"allows":[92],"employing":[93],"personalized":[95,210],"relaxed":[96,211],"initialization":[97,212],"state":[98,112,120],"at":[99],"beginning":[101],"each":[103],"stage.":[106],"Specifically,":[107],"FedInit":[108,189],"initializes":[109],"moving":[114],"away":[115],"current":[118,219],"towards":[121],"reverse":[123],"direction":[124],"latest":[127],"state.":[129],"Moreover,":[130],"further":[132],"understand":[133],"how":[134],"inconsistency":[135],"disrupts":[136],"performance":[137,226],"introduce":[141],"excess":[143],"risk":[144],"study":[147],"divergence":[149],"term":[150],"investigate":[152],"test":[154],"error":[155,163,177],"FL.":[157],"Our":[158],"studies":[159],"show":[160],"optimization":[162],"not":[165],"sensitive":[166],"inconsistency,":[170],"while":[171],"mainly":[173],"affects":[174],"generalization":[176,225],"bound.":[178],"Extensive":[179],"experiments":[180],"are":[181],"conducted":[182],"validate":[184],"efficiency.":[186],"The":[187],"proposed":[188],"method":[190],"could":[191,213],"achieve":[192,223],"comparable":[193],"results":[194],"compared":[195],"several":[197,218],"advanced":[198,220],"benchmarks":[199],"without":[200],"any":[201],"additional":[202],"or":[204],"communication":[205],"costs.":[206],"Meanwhile,":[207],"also":[214],"be":[215],"incorporated":[216],"into":[217],"algorithms":[221],"higher":[224],"paradigm.":[230]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-16T00:00:00"}
