{"id":"https://openalex.org/W4390463213","doi":"https://doi.org/10.1587/transinf.2023mul0002","title":"Unbiased Pseudo-Labeling for Learning with Noisy Labels","display_name":"Unbiased Pseudo-Labeling for Learning with Noisy Labels","publication_year":2023,"publication_date":"2023-12-31","ids":{"openalex":"https://openalex.org/W4390463213","doi":"https://doi.org/10.1587/transinf.2023mul0002"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2023mul0002","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2023mul0002","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/1/E107.D_2023MUL0002/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/1/E107.D_2023MUL0002/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075336771","display_name":"Ryota Higashimoto","orcid":"https://orcid.org/0009-0003-6307-4461"},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryota HIGASHIMOTO","raw_affiliation_strings":["Faculty of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061967814","display_name":"Soh Yoshida","orcid":"https://orcid.org/0000-0003-0237-7461"},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Soh YOSHIDA","raw_affiliation_strings":["Faculty of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093625286","display_name":"Takashi Horihata","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi HORIHATA","raw_affiliation_strings":["Faculty of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089184180","display_name":"Mitsuji Muneyasu","orcid":"https://orcid.org/0000-0002-4492-5991"},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mitsuji MUNEYASU","raw_affiliation_strings":["Faculty of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7089,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67973614,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"E107.D","issue":"1","first_page":"44","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9710999727249146,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9466000199317932,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.835297703742981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6548165082931519},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5688518285751343},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5202304720878601},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5197243690490723},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5033144354820251},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.49604758620262146},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4524950683116913},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4341023564338684},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4309491217136383},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39885225892066956},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37672680616378784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10358837246894836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.835297703742981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6548165082931519},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5688518285751343},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5202304720878601},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5197243690490723},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5033144354820251},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.49604758620262146},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4524950683116913},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4341023564338684},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4309491217136383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39885225892066956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37672680616378784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10358837246894836},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2023mul0002","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2023mul0002","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/1/E107.D_2023MUL0002/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2023mul0002","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2023mul0002","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/1/E107.D_2023MUL0002/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G503899748","display_name":"A Basic Study on the Analysis of Writing Style of Excavated Wooden slips from China","funder_award_id":"19K01044","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8237952253","display_name":null,"funder_award_id":"22K18007","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4390463213.pdf"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1996016456","https://openalex.org/W2302255633","https://openalex.org/W2682189153","https://openalex.org/W2803237185","https://openalex.org/W2911830322","https://openalex.org/W2943865428","https://openalex.org/W2950220847","https://openalex.org/W2963096987","https://openalex.org/W2963735582","https://openalex.org/W2978426779","https://openalex.org/W2996108195","https://openalex.org/W3001197829","https://openalex.org/W3118608800","https://openalex.org/W3137695714","https://openalex.org/W4210691876","https://openalex.org/W4312754496"],"related_works":["https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W3042419602","https://openalex.org/W2966649771","https://openalex.org/W2803237185","https://openalex.org/W2963735582","https://openalex.org/W3113301541","https://openalex.org/W4288260397","https://openalex.org/W1989345694"],"abstract_inverted_index":{"Noisy":[0],"labels":[1,21,43,60,163],"in":[2,82,148,179],"training":[3,34,126],"data":[4,35,40,48,111,115,127],"can":[5,102,144],"significantly":[6],"harm":[7],"the":[8,28,33,58,66,70,79,97,100,122,125,129,146,186],"performance":[9,150],"of":[10,25,39,47,69,99,124,137],"deep":[11],"neural":[12],"networks":[13],"(DNNs).":[14],"Recent":[15],"research":[16],"on":[17,94,169,185],"learning":[18,55,159],"with":[19,41,49,161],"noisy":[20,154,162],"uses":[22],"a":[23,37,45,114,158],"property":[24],"DNNs":[26],"called":[27],"memorization":[29],"effect":[30],"to":[31],"divide":[32],"into":[36],"set":[38,46],"reliable":[42],"and":[44,61,190],"unreliable":[50,59],"labels.":[51],"Methods":[52],"introducing":[53],"semi-supervised":[54,75,130],"strategies":[56],"discard":[57],"assign":[62],"pseudo-labels":[63,101],"generated":[64],"from":[65,121,141],"confident":[67],"predictions":[68],"model.":[71],"So":[72],"far,":[73],"this":[74,83],"strategy":[76],"has":[77],"yielded":[78],"best":[80],"results":[81],"field.":[84],"However,":[85],"we":[86,133,143],"observe":[87],"that":[88,107,119,139,164],"even":[89],"when":[90],"models":[91],"are":[92],"trained":[93],"balanced":[95],"data,":[96],"distribution":[98],"still":[103],"exhibit":[104],"an":[105],"imbalance":[106],"is":[108,117],"driven":[109],"by":[110,152],"similarity.":[112],"Additionally,":[113],"bias":[116,138],"seen":[118],"originates":[120],"division":[123],"using":[128],"method.":[131],"If":[132],"address":[134],"both":[135],"types":[136],"arise":[140],"pseudo-labels,":[142],"avoid":[145],"decrease":[147],"generalization":[149],"caused":[151],"biased":[153],"pseudo-labels.":[155],"We":[156],"propose":[157],"method":[160,174],"introduces":[165],"unbiased":[166],"pseudo-labeling":[167],"based":[168],"causal":[170],"inference.":[171],"The":[172],"proposed":[173],"achieves":[175],"significant":[176],"accuracy":[177],"gains":[178],"experiments":[180],"at":[181],"high":[182],"noise":[183],"rates":[184],"standard":[187],"benchmarks":[188],"CIFAR-10":[189],"CIFAR-100.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}