{"id":"https://openalex.org/W4400528018","doi":"https://doi.org/10.1109/ainit61980.2024.10581615","title":"Adversarial Federated Learning Algorithms for Non-IID Data","display_name":"Adversarial Federated Learning Algorithms for Non-IID Data","publication_year":2024,"publication_date":"2024-03-29","ids":{"openalex":"https://openalex.org/W4400528018","doi":"https://doi.org/10.1109/ainit61980.2024.10581615"},"language":"en","primary_location":{"id":"doi:10.1109/ainit61980.2024.10581615","doi":"https://doi.org/10.1109/ainit61980.2024.10581615","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ainit61980.2024.10581615","pdf_url":null,"source":{"id":"https://openalex.org/S4363606068","display_name":"International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5104348068","display_name":"Zishi Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zishi Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Hefei University of Technology,Hefei Province,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hefei University of Technology,Hefei Province,China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033333041","display_name":"Renbin Zhang","orcid":"https://orcid.org/0000-0003-3651-2609","observed_orcids":["https://orcid.org/0000-0003-3651-2609"]},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renbin Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Hefei University of Technology,Hefei Province,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hefei University of Technology,Hefei Province,China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102384729","display_name":"Yuhang Cui","orcid":"https://orcid.org/0009-0001-9649-8098","observed_orcids":["https://orcid.org/0009-0001-9649-8098"]},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Cui","raw_affiliation_strings":["School of Computer Science and Technology, Hefei University of Technology,Hefei Province,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hefei University of Technology,Hefei Province,China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06330007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"740","last_page":"745"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994999766349792,"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":0.9994999766349792,"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":9.999999747378752e-05,"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":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/federated-learning","display_name":"federated learning","score":0.9800000190734863},{"id":"https://openalex.org/keywords/non-iid-data","display_name":"non-IID data","score":0.9869999885559082},{"id":"https://openalex.org/keywords/data-heterogeneity","display_name":"data heterogeneity","score":0.9869999885559082},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"adversarial learning","score":0.9779999852180481},{"id":"https://openalex.org/keywords/discriminator","display_name":"discriminator","score":0.847000002861023},{"id":"https://openalex.org/keywords/model-bias","display_name":"model bias","score":0.9169999957084656},{"id":"https://openalex.org/keywords/feature-fusion","display_name":"feature fusion","score":0.7020000219345093},{"id":"https://openalex.org/keywords/communication-overhead-reduction","display_name":"communication cost reduction","score":0.7369999885559082},{"id":"https://openalex.org/keywords/local-models","display_name":"local models","score":0.3840000033378601}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8025653958320618},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7813948392868042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5177189707756042},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4014939069747925},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3855676054954529},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.353106826543808}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ainit61980.2024.10581615","doi":"https://doi.org/10.1109/ainit61980.2024.10581615","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ainit61980.2024.10581615","pdf_url":null,"source":{"id":"https://openalex.org/S4363606068","display_name":"International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W3041100787","https://openalex.org/W3045317090","https://openalex.org/W3196371845","https://openalex.org/W3204874618","https://openalex.org/W4221158339","https://openalex.org/W4229029907"],"related_works":["https://openalex.org/W4387608618","https://openalex.org/W6922480507","https://openalex.org/W4390190963","https://openalex.org/W4376478419","https://openalex.org/W4285817572","https://openalex.org/W4417509596","https://openalex.org/W4283078013","https://openalex.org/W4414876130","https://openalex.org/W4317434693","https://openalex.org/W4407576296"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,15,32,42,45,49,56,70,87,90,95,99,103,118,123,142,152],"problems":[3,153],"of":[4,11,17,72,89],"poor":[5],"performance":[6],"and":[7,40,48,111],"high":[8],"communication":[9,104,138],"cost":[10],"federated":[12,25,120],"learning":[13,26,121],"under":[14,60],"condition":[16],"data":[18,113,156],"heterogeneity":[19],"(non-IID),":[20],"this":[21,126,145],"paper":[22,127,146],"proposes":[23],"a":[24,36,80],"algorithm":[27,124,143],"based":[28,108],"on":[29,109],"adversarial":[30],"learning:":[31],"local":[33,46,73,100],"model":[34,47,51,57,97],"uses":[35],"discriminator":[37,63],"to":[38,54,68,78,85,98,101,149],"extract":[39],"amplify":[41],"difference":[43],"between":[44],"global":[50,76],"in":[52,125,144],"order":[53],"improve":[55,86],"bias":[58],"problem":[59],"non-IID.":[61],"The":[62],"output":[64],"is":[65,147],"also":[66],"used":[67],"guide":[69],"fusion":[71,83],"features":[74,77],"with":[75,117,134],"construct":[79],"dynamic":[81],"feature":[82],"mechanism":[84],"accuracy":[88,130],"model.":[91],"In":[92],"addition,":[93],"restricting":[94],"discriminative":[96],"reduce":[102],"cost.":[105],"Experimental":[106],"results":[107],"CIFAR-10":[110],"CIFAR-100":[112],"show":[114],"that":[115,141],"compared":[116],"state-of-the-art":[119],"algorithms,":[122],"improves":[128],"its":[129],"by":[131,155],"about":[132],"2%-3%":[133],"almost":[135],"no":[136],"additional":[137],"resources,":[139],"indicating":[140],"able":[148],"effectively":[150],"mitigate":[151],"caused":[154],"heterogeneity.":[157]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2024-07-12T00:00:00"}
