{"id":"https://openalex.org/W4385767857","doi":"https://doi.org/10.24963/ijcai.2023/492","title":"FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity","display_name":"FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385767857","doi":"https://doi.org/10.24963/ijcai.2023/492"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/492","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/492","pdf_url":"https://www.ijcai.org/proceedings/2023/0492.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0492.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103082365","display_name":"Nannan Wu","orcid":"https://orcid.org/0000-0003-4254-528X"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nannan Wu","raw_affiliation_strings":["School of Electronic Information and Communications, Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Communications, Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091921038","display_name":"Li Yu","orcid":"https://orcid.org/0000-0002-3912-4305"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yu","raw_affiliation_strings":["School of Electronic Information and Communications, Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Communications, Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101765429","display_name":"Xuefeng Jiang","orcid":"https://orcid.org/0000-0002-0211-9123"},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Jiang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077687075","display_name":"Kwang\u2010Ting Cheng","orcid":"https://orcid.org/0000-0002-3885-4912"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kwang-Ting Cheng","raw_affiliation_strings":["School of Engineering, Hong Kong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079057344","display_name":"Zengqiang Yan","orcid":"https://orcid.org/0000-0002-2039-3863"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengqiang Yan","raw_affiliation_strings":["School of Electronic Information and Communications, Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Communications, Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4424","last_page":"4432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9993000030517578,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9993000030517578,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9965999722480774,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9927999973297119,"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/computer-science","display_name":"Computer science","score":0.8164458274841309},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7177400588989258},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.640425443649292},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5623581409454346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5105329751968384},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.454525351524353},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.43907785415649414},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4347289204597473},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.25794851779937744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8164458274841309},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7177400588989258},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.640425443649292},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5623581409454346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5105329751968384},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.454525351524353},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.43907785415649414},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4347289204597473},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.25794851779937744},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2023/492","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/492","pdf_url":"https://www.ijcai.org/proceedings/2023/0492.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-130405","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-130405","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/492","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/492","pdf_url":"https://www.ijcai.org/proceedings/2023/0492.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G3236001388","display_name":null,"funder_award_id":"62271220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3578521231","display_name":null,"funder_award_id":"2022CFB585","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G8019045571","display_name":null,"funder_award_id":"62202179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null},{"id":"https://openalex.org/F4320323537","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385767857.pdf"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2084434464","https://openalex.org/W2194775991","https://openalex.org/W2765407302","https://openalex.org/W2804268522","https://openalex.org/W2951970475","https://openalex.org/W2963160702","https://openalex.org/W2963466845","https://openalex.org/W2963735582","https://openalex.org/W2963946669","https://openalex.org/W2964416181","https://openalex.org/W2970941190","https://openalex.org/W2981873476","https://openalex.org/W2989289980","https://openalex.org/W2992996860","https://openalex.org/W2995197345","https://openalex.org/W2996108195","https://openalex.org/W3003380256","https://openalex.org/W3006555759","https://openalex.org/W3033511014","https://openalex.org/W3034321207","https://openalex.org/W3038022836","https://openalex.org/W3102785203","https://openalex.org/W3107887114","https://openalex.org/W3122855191","https://openalex.org/W3129603732","https://openalex.org/W3169682907","https://openalex.org/W3175272368","https://openalex.org/W3176639943","https://openalex.org/W3195098128","https://openalex.org/W3204597713","https://openalex.org/W3215126987","https://openalex.org/W4212881588","https://openalex.org/W4232415764","https://openalex.org/W4281384403","https://openalex.org/W4283694663","https://openalex.org/W4287123304","https://openalex.org/W4287828713","https://openalex.org/W4293791267","https://openalex.org/W4297687186","https://openalex.org/W4304207335","https://openalex.org/W4312231739","https://openalex.org/W4312403682","https://openalex.org/W4312462223","https://openalex.org/W4312464225","https://openalex.org/W4312907849","https://openalex.org/W4313066544","https://openalex.org/W4313068152","https://openalex.org/W4318619660"],"related_works":["https://openalex.org/W2572355887","https://openalex.org/W2327107878","https://openalex.org/W2171117985","https://openalex.org/W1526760723","https://openalex.org/W2012356576","https://openalex.org/W2126659863","https://openalex.org/W3112120395","https://openalex.org/W4385670989","https://openalex.org/W2102487628","https://openalex.org/W2009680848"],"abstract_inverted_index":{"Federated":[0],"noisy":[1,93],"label":[2,32,50,59,139],"learning":[3],"(FNLL)":[4],"is":[5,56,61],"emerging":[6],"as":[7],"a":[8,44,66,103],"promising":[9],"tool":[10],"for":[11,71,92,110,134],"privacy-preserving":[12],"multi-source":[13],"decentralized":[14],"learning.":[15,74],"Existing":[16],"research,":[17],"relying":[18],"on":[19,117],"the":[20,77,97,118,125,130],"assumption":[21],"of":[22,80,127],"class-balanced":[23],"global":[24,54],"data,":[25],"might":[26],"be":[27],"incapable":[28],"to":[29],"model":[30,113],"complicated":[31],"noise,":[33],"especially":[34],"in":[35,76,142],"medical":[36],"scenarios.":[37,145],"In":[38,96],"this":[39],"paper,":[40],"we":[41],"first":[42,78],"formulate":[43],"new":[45],"and":[46,58,63,102,121,138],"more":[47],"realistic":[48],"federated":[49,73,112],"noise":[51,60,140],"problem":[52],"where":[53],"data":[55],"class-imbalanced":[57],"heterogeneous,":[62],"then":[64],"propose":[65],"two-stage":[67],"framework":[68],"named":[69],"FedNoRo":[70,128],"noise-robust":[72,111],"Specifically,":[75],"stage":[79],"FedNoRo,":[81],"per-class":[82],"loss":[83],"indicators":[84],"followed":[85],"by":[86],"Gaussian":[87],"Mixture":[88],"Model":[89],"are":[90,107],"deployed":[91],"client":[94],"identification.":[95],"second":[98],"stage,":[99],"knowledge":[100],"distillation":[101],"distance-aware":[104],"aggregation":[105],"function":[106],"jointly":[108],"adopted":[109],"updating.":[114],"Experimental":[115],"results":[116],"widely-used":[119],"ICH":[120],"ISIC2019":[122],"datasets":[123],"demonstrate":[124],"superiority":[126],"against":[129],"state-of-the-art":[131],"FNLL":[132],"methods":[133],"addressing":[135],"class":[136],"imbalance":[137],"heterogeneity":[141],"real-world":[143],"FL":[144]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":14}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}