{"id":"https://openalex.org/W2995812976","doi":"https://doi.org/10.1109/icpr48806.2021.9412747","title":"Towards Robust Learning with Different Label Noise Distributions","display_name":"Towards Robust Learning with Different Label Noise Distributions","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W2995812976","doi":"https://doi.org/10.1109/icpr48806.2021.9412747","mag":"2995812976"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.08741","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028186506","display_name":"Diego Ortego","orcid":"https://orcid.org/0000-0002-1011-3610"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Diego Ortego","raw_affiliation_strings":["Insight Centre for Data Analytics, Dublin City University (DCU)"],"affiliations":[{"raw_affiliation_string":"Insight Centre for Data Analytics, Dublin City University (DCU)","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015739552","display_name":"Eric Arazo","orcid":"https://orcid.org/0000-0001-9769-3592"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Eric Arazo","raw_affiliation_strings":["Insight Centre for Data Analytics, Dublin City University (DCU)"],"affiliations":[{"raw_affiliation_string":"Insight Centre for Data Analytics, Dublin City University (DCU)","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015341418","display_name":"Paul Albert","orcid":"https://orcid.org/0000-0001-8220-272X"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Paul Albert","raw_affiliation_strings":["Insight Centre for Data Analytics, Dublin City University (DCU)"],"affiliations":[{"raw_affiliation_string":"Insight Centre for Data Analytics, Dublin City University (DCU)","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106498523","display_name":"Noel E. O\u2019Connor","orcid":"https://orcid.org/0000-0002-4033-9135"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Noel E. O'Connor","raw_affiliation_strings":["Insight Centre for Data Analytics, Dublin City University (DCU)"],"affiliations":[{"raw_affiliation_string":"Insight Centre for Data Analytics, Dublin City University (DCU)","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073924795","display_name":"Kevin McGuinness","orcid":"https://orcid.org/0000-0003-1336-6477"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Kevin McGuinness","raw_affiliation_strings":["Insight Centre for Data Analytics, Dublin City University (DCU)"],"affiliations":[{"raw_affiliation_string":"Insight Centre for Data Analytics, Dublin City University (DCU)","institution_ids":["https://openalex.org/I42934936"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5028186506"],"corresponding_institution_ids":["https://openalex.org/I42934936"],"apc_list":null,"apc_paid":null,"fwci":0.8398,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77571388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"7020","last_page":"7027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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":0.9987999796867371,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9858999848365784,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9848999977111816,"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/noise","display_name":"Noise (video)","score":0.797014594078064},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7943778038024902},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7747703194618225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5746880173683167},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5369415283203125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.514076828956604},{"id":"https://openalex.org/keywords/memorization","display_name":"Memorization","score":0.4884892702102661},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4748378396034241},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.44800126552581787},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38953542709350586},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3507937788963318},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.18501326441764832},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12285873293876648}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.797014594078064},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7943778038024902},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7747703194618225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5746880173683167},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5369415283203125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.514076828956604},{"id":"https://openalex.org/C30038468","wikidata":"https://www.wikidata.org/wiki/Q4354775","display_name":"Memorization","level":2,"score":0.4884892702102661},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4748378396034241},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.44800126552581787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38953542709350586},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3507937788963318},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.18501326441764832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12285873293876648},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1912.08741","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.08741","pdf_url":"https://arxiv.org/pdf/1912.08741","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:doras.dcu.ie:25086","is_oa":true,"landing_page_url":"http://doras.dcu.ie/25086/","pdf_url":"http://doras.dcu.ie/25086/1/CameraReady_ICPR20.pdf","source":{"id":"https://openalex.org/S4306401511","display_name":"Dublin City University Open Access Institutional Repository (Dublin City University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I42934936","host_organization_name":"Dublin City University","host_organization_lineage":["https://openalex.org/I42934936"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"  Ortego, Diego ORCID: 0000-0002-1011-3610 <https://orcid.org/0000-0002-1011-3610>, Arazo, Eric, Albert, Paul, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135> and McGuinness, Kevin ORCID: 0000-0003-1336-6477 <https://orcid.org/0000-0003-1336-6477>  (2021) Towards robust learning with different label noise distributions.  In: International Conference on Pattern Recognition (ICPR) 2020, 10-15 Jan 2021, Milan, Italy (Online).      ","raw_type":"Conference or Workshop Item"},{"id":"mag:2995812976","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1912.08741","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1912.08741","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1912.08741","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.08741","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.08741","pdf_url":"https://arxiv.org/pdf/1912.08741","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G6371842503","display_name":null,"funder_award_id":"SFI/15/SIRG/3283,SFI/12/RC/2289_P2","funder_id":"https://openalex.org/F4320320847","funder_display_name":"Science Foundation Ireland"}],"funders":[{"id":"https://openalex.org/F4320320847","display_name":"Science Foundation Ireland","ror":"https://ror.org/0271asj38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1921293667","https://openalex.org/W2108598243","https://openalex.org/W2163922914","https://openalex.org/W2167460663","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2302255633","https://openalex.org/W2342662179","https://openalex.org/W2439114332","https://openalex.org/W2558661413","https://openalex.org/W2560023338","https://openalex.org/W2575671312","https://openalex.org/W2577784528","https://openalex.org/W2743200750","https://openalex.org/W2783126922","https://openalex.org/W2785495800","https://openalex.org/W2786808285","https://openalex.org/W2798820905","https://openalex.org/W2887842788","https://openalex.org/W2905290040","https://openalex.org/W2913939497","https://openalex.org/W2941387380","https://openalex.org/W2943997064","https://openalex.org/W2945007112","https://openalex.org/W2962762541","https://openalex.org/W2963037989","https://openalex.org/W2963081269","https://openalex.org/W2963096987","https://openalex.org/W2963399829","https://openalex.org/W2963446712","https://openalex.org/W2963537932","https://openalex.org/W2963659419","https://openalex.org/W2963735582","https://openalex.org/W2963759070","https://openalex.org/W2963916161","https://openalex.org/W2964096266","https://openalex.org/W2964155802","https://openalex.org/W2964274690","https://openalex.org/W2964292098","https://openalex.org/W2967052791","https://openalex.org/W2978290191","https://openalex.org/W2978426779","https://openalex.org/W2981952612","https://openalex.org/W2990019157","https://openalex.org/W2996108195","https://openalex.org/W3091002423","https://openalex.org/W3118608800","https://openalex.org/W6640298173","https://openalex.org/W6678280073","https://openalex.org/W6698183232","https://openalex.org/W6738763127","https://openalex.org/W6740005241","https://openalex.org/W6745136726","https://openalex.org/W6751420435","https://openalex.org/W6751647823","https://openalex.org/W6753772092","https://openalex.org/W6762161020","https://openalex.org/W6762563763","https://openalex.org/W6762892961","https://openalex.org/W6762913911","https://openalex.org/W6763485134","https://openalex.org/W6767203202","https://openalex.org/W6771630921"],"related_works":["https://openalex.org/W3163007724","https://openalex.org/W2743200750","https://openalex.org/W3118608800","https://openalex.org/W3035702670","https://openalex.org/W3132170818","https://openalex.org/W3129603874","https://openalex.org/W3170414933","https://openalex.org/W3194010558","https://openalex.org/W3195624971","https://openalex.org/W2967052791","https://openalex.org/W3121661476","https://openalex.org/W2955385886","https://openalex.org/W3174485549","https://openalex.org/W3201674335","https://openalex.org/W3006035290","https://openalex.org/W2767183759","https://openalex.org/W3164866731","https://openalex.org/W2972510403","https://openalex.org/W3172754087","https://openalex.org/W3154887629"],"abstract_inverted_index":{"Noisy":[0],"labels":[1,26],"are":[2,48,148],"an":[3,13,112],"unavoidable":[4],"consequence":[5],"of":[6,72,123],"labeling":[7],"processes":[8],"and":[9,77,103,131,141,159],"detecting":[10],"them":[11],"is":[12,93,181],"important":[14],"step":[15],"towards":[16],"preventing":[17],"performance":[18],"degradations":[19],"in":[20,40,143,156],"Convolutional":[21],"Neural":[22],"Networks.":[23],"Discarding":[24],"noisy":[25],"avoids":[27],"a":[28,41,59,86],"harmful":[29],"memorization,":[30],"while":[31],"the":[32,52,70,100,107,121,165],"associated":[33],"image":[34],"content":[35],"can":[36],"still":[37],"be":[38],"exploited":[39],"semi-supervised":[42],"learning":[43,125],"(SSL)":[44],"setup.":[45],"Clean":[46],"samples":[47],"usually":[49],"identified":[50],"using":[51],"small":[53],"loss":[54,88],"trick,":[55],"i.e.":[56],"they":[57],"exhibit":[58],"low":[60],"loss.":[61],"However,":[62],"we":[63],"show":[64],"that":[65,133,142,164],"different":[66],"noise":[67,129,136,140,153,168],"distributions":[68,130],"make":[69],"application":[71],"this":[73],"trick":[74],"less":[75],"straightforward":[76],"propose":[78],"to":[79,84,98],"continuously":[80],"relabel":[81],"all":[82],"images":[83],"reveal":[85],"discriminative":[87],"against":[89],"multiple":[90],"distributions.":[91],"SSL":[92],"then":[94],"applied":[95],"twice,":[96],"once":[97],"improve":[99],"clean-noisy":[101],"detection":[102],"again":[104],"for":[105,118],"training":[106],"final":[108],"model.":[109],"We":[110],"design":[111],"experimental":[113],"setup":[114],"based":[115],"on":[116],"ImageNet32/64":[117,158],"better":[119,137],"understanding":[120],"consequences":[122],"representation":[124],"with":[126],"differing":[127],"label":[128,152,167],"find":[132],"non-uniform":[134],"out-of-distribution":[135],"resembles":[138],"real-world":[139],"most":[144],"cases":[145],"intermediate":[146],"features":[147],"not":[149],"affected":[150],"by":[151],"corruption.":[154],"Experiments":[155],"CIFAR-10/100,":[157],"WebVision":[160],"(real-world":[161],"noise)":[162],"demonstrate":[163],"proposed":[166],"Distribution":[169],"Robust":[170],"Pseudo-Labeling":[171],"(DRPL)":[172],"approach":[173],"gives":[174],"substantial":[175],"improvements":[176],"over":[177],"recent":[178],"state-of-the-art.":[179],"Code":[180],"available":[182],"at":[183],"https://git.io/JJ0PV.":[184]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}