{"id":"https://openalex.org/W4392699550","doi":"https://doi.org/10.1145/3615593.3615721","title":"Gradient Calibration for Non-I.I.D. Federated Learning","display_name":"Gradient Calibration for Non-I.I.D. Federated Learning","publication_year":2023,"publication_date":"2023-10-06","ids":{"openalex":"https://openalex.org/W4392699550","doi":"https://doi.org/10.1145/3615593.3615721"},"language":"en","primary_location":{"id":"doi:10.1145/3615593.3615721","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615593.3615721","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615593.3615721","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3615593.3615721","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077793588","display_name":"Jiachen Li","orcid":"https://orcid.org/0000-0003-3332-475X"},"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":"Jiachen Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":"https://orcid.org/0000-0003-3332-475X","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100649609","display_name":"Yuchao Zhang","orcid":"https://orcid.org/0000-0002-0135-8915"},"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":"Yuchao Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":"https://orcid.org/0000-0002-0135-8915","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068062051","display_name":"Yiping Li","orcid":"https://orcid.org/0000-0003-1397-0527"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiping Li","raw_affiliation_strings":["University of Washington"],"raw_orcid":"https://orcid.org/0000-0003-1397-0527","affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006019956","display_name":"Xiangyang Gong","orcid":"https://orcid.org/0000-0002-0631-9747"},"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":"Xiangyang Gong","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":"https://orcid.org/0000-0002-0631-9747","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100329067","display_name":"Wendong Wang","orcid":"https://orcid.org/0000-0002-6418-8087"},"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":"Wendong Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":"https://orcid.org/0000-0002-6418-8087","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"119","last_page":"124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9983000159263611,"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/T10237","display_name":"Cryptography and Data Security","score":0.9767000079154968,"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/calibration","display_name":"Calibration","score":0.7334686517715454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6523450016975403},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3223878741264343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10776090621948242},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07890650629997253}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7334686517715454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6523450016975403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3223878741264343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10776090621948242},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07890650629997253}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3615593.3615721","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615593.3615721","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615593.3615721","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3615593.3615721","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615593.3615721","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615593.3615721","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392699550.pdf","grobid_xml":"https://content.openalex.org/works/W4392699550.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W2979359324","https://openalex.org/W3021654819","https://openalex.org/W3092189037","https://openalex.org/W3112044954","https://openalex.org/W3128577478"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Federated":[0,93,132,168],"learning":[1],"(FL)":[2],"has":[3,173],"yielded":[4],"impressive":[5],"results":[6],"in":[7,74,76,157,182],"recent":[8],"years.":[9],"However,":[10],"its":[11],"effectiveness":[12,164],"on":[13,83,124],"non-independently":[14],"and":[15,80,104,128,141],"identically":[16],"distributed":[17],"(non-i.i.d)":[18],"data":[19,65,187],"remains":[20],"challenging.":[21],"Existing":[22],"work":[23],"aims":[24],"to":[25,35,50,97],"address":[26],"this":[27,56,84],"challenge":[28,62,101],"through":[29],"client":[30,37,53],"selection":[31],"strategies":[32],"or":[33],"modifications":[34],"the":[36,61,92,99,113,131,150,163,166,178],"objective":[38],"function.":[39],"Despite":[40],"these":[41],"efforts,":[42],"we":[43,58,86,118],"contend":[44],"that":[45,60,130],"existing":[46],"methods":[47],"are":[48],"unable":[49],"fully":[51],"leverage":[52],"gradients.":[54],"In":[55],"paper,":[57],"posit":[59],"of":[63,115,122,152,165,180],"non-i.i.d":[64,100,126,158,186],"stems":[66],"primarily":[67],"from":[68],"conflicting":[69,106,155],"gradients":[70,107,156],"among":[71],"clients,":[72],"resulting":[73],"deviations":[75],"both":[77],"gradient":[78],"magnitude":[79],"direction.":[81],"Building":[82],"insight,":[85],"propose":[87],"a":[88,120],"simple":[89],"plug-in,":[90],"named":[91],"Gradient":[94,133,169],"Tailor":[95,134],"(FGT),":[96],"mitigate":[98],"by":[102,139],"identifying":[103],"calibrating":[105],"before":[108],"federated":[109],"aggregation.":[110],"To":[111],"evaluate":[112],"efficacy":[114],"our":[116],"approach,":[117],"conduct":[119],"series":[121],"experiments":[123],"simulated":[125],"datasets":[127],"demonstrate":[129],"significantly":[135],"improves":[136],"inference":[137],"accuracy":[138],"5%":[140],"achieves":[142],"6":[143],"times":[144],"convergence":[145],"speedup.":[146],"Our":[147],"findings":[148],"highlight":[149],"value":[151],"explicitly":[153],"addressing":[154],"data,":[159],"as":[160,162],"well":[161],"proposed":[167],"Tailor.":[170],"This":[171],"contribution":[172],"implications":[174],"for":[175],"further":[176],"enhancing":[177],"performance":[179],"FL":[181],"real-world":[183],"settings":[184],"with":[185],"distributions.":[188]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}