{"id":"https://openalex.org/W4403390133","doi":"https://doi.org/10.1109/lsp.2024.3480033","title":"Hierarchical Noise-Tolerant Meta-Learning With Noisy Labels","display_name":"Hierarchical Noise-Tolerant Meta-Learning With Noisy Labels","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403390133","doi":"https://doi.org/10.1109/lsp.2024.3480033"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2024.3480033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3480033","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","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/A5100375489","display_name":"Yahui Liu","orcid":"https://orcid.org/0000-0001-7787-584X"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yahui Liu","raw_affiliation_strings":["Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101653839","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0003-1281-2287"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101841176","display_name":"Yong Yang","orcid":"https://orcid.org/0000-0001-5698-6751"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuntai Yang","raw_affiliation_strings":["Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081346369","display_name":"Renlong Wang","orcid":"https://orcid.org/0000-0002-6144-6028"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renlong Wang","raw_affiliation_strings":["Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015448716","display_name":"Simiao Wang","orcid":"https://orcid.org/0009-0001-4210-7960"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Simiao Wang","raw_affiliation_strings":["College of Artificial Intelligence, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100375489"],"corresponding_institution_ids":["https://openalex.org/I10660446"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67791688,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"31","issue":null,"first_page":"3020","last_page":"3024"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9153000116348267,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9153000116348267,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9128000140190125,"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":0.6754220128059387},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6390128135681152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49422505497932434},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.46680644154548645},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41717177629470825},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3566453456878662},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35500454902648926},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.29376664757728577}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6754220128059387},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6390128135681152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49422505497932434},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.46680644154548645},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41717177629470825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3566453456878662},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35500454902648926},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.29376664757728577},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2024.3480033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3480033","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5464785614","display_name":null,"funder_award_id":"62406051","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6627029586","display_name":null,"funder_award_id":"62372077","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2295107390","https://openalex.org/W2302255633","https://openalex.org/W2978625989","https://openalex.org/W3042609801","https://openalex.org/W3046688540","https://openalex.org/W3139144418","https://openalex.org/W3170414933","https://openalex.org/W3171635822","https://openalex.org/W3172778040","https://openalex.org/W3175103763","https://openalex.org/W3216552527","https://openalex.org/W4214585162","https://openalex.org/W4312227358","https://openalex.org/W4312753781","https://openalex.org/W4312766345","https://openalex.org/W4313022252","https://openalex.org/W4313068152","https://openalex.org/W4313135270","https://openalex.org/W4382240011","https://openalex.org/W4386071515","https://openalex.org/W4386071642","https://openalex.org/W4386075521","https://openalex.org/W4387339740","https://openalex.org/W4388430863","https://openalex.org/W4388983767","https://openalex.org/W4389879572","https://openalex.org/W4391090497","https://openalex.org/W4394967126","https://openalex.org/W6771630921","https://openalex.org/W6781063151"],"related_works":["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","https://openalex.org/W2150465873"],"abstract_inverted_index":{"Due":[0],"to":[1,111,115,140,165],"the":[2,9,83,99,107,121,144,148,156],"detrimental":[3],"impact":[4],"of":[5,11,151],"noisy":[6,17,39,166,175],"labels":[7,18],"on":[8,73,170],"generalization":[10],"deep":[12,26],"neural":[13],"networks,":[14],"learning":[15,27],"with":[16,61],"has":[19],"become":[20],"an":[21],"important":[22],"task":[23],"in":[24,143],"modern":[25],"applications.":[28],"Many":[29],"previous":[30,184],"efforts":[31],"have":[32],"mitigated":[33],"this":[34,45,49,74],"problem":[35],"by":[36],"either":[37],"removing":[38],"samples":[40,66],"or":[41],"correcting":[42],"labels.":[43,167],"In":[44,98,120],"letter,":[46],"we":[47,76,102,124,153],"address":[48],"issue":[50],"from":[51],"a":[52,78,91,135],"new":[53,136],"perspective":[54],"and":[55,64,96,133,173],"empirically":[56],"find":[57],"that":[58,155,162],"models":[59],"trained":[60],"both":[62,171],"clean":[63],"mislabeled":[65],"exhibit":[67],"distinguishable":[68],"activation":[69,126,131],"feature":[70,127,160],"distributions.":[71],"Building":[72],"observation,":[75],"propose":[77,134],"novel":[79],"meta-learning":[80],"approach":[81],"called":[82],"Hierarchical":[84],"Noise-tolerant":[85],"Meta-Learning":[86],"(HNML)":[87],"method,":[88],"which":[89],"involves":[90],"bi-level":[92,149],"optimization":[93,150],"comprising":[94],"meta-training":[95,100],"meta-testing.":[97],"stage,":[101,123],"incorporate":[103],"consistency":[104],"loss":[105],"at":[106],"output":[108],"prediction":[109],"hierarchy":[110],"facilitate":[112],"model":[113,157],"adaptation":[114],"dynamically":[116],"changing":[117],"label":[118],"noise.":[119],"meta-testing":[122],"extract":[125],"distributions":[128],"using":[129],"class":[130],"maps":[132],"mask-guided":[137],"self-learning":[138],"method":[139,179],"correct":[141],"biases":[142],"foreground":[145],"regions.":[146],"Through":[147],"HNML,":[152],"ensure":[154],"generates":[158],"discriminative":[159],"representations":[161],"are":[163],"insensitive":[164],"When":[168],"evaluated":[169],"synthetic":[172],"real-world":[174],"datasets,":[176],"our":[177],"HNML":[178],"achieves":[180],"significant":[181],"improvements":[182],"over":[183],"state-of-the-art":[185],"methods.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
