{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T07:13:42Z","timestamp":1775200422138,"version":"3.50.1"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000646","name":"Japan Society for the Promotion of Science (JSPS), KAKENHI, Japan","doi-asserted-by":"publisher","award":["22K18007"],"award-info":[{"award-number":["22K18007"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000646","name":"Japan Society for the Promotion of Science (JSPS), KAKENHI, Japan","doi-asserted-by":"publisher","award":["25K00510"],"award-info":[{"award-number":["25K00510"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2026.3676403","type":"journal-article","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T20:09:20Z","timestamp":1774296560000},"page":"45449-45463","source":"Crossref","is-referenced-by-count":0,"title":["Feature Space-Preserving Machine Unlearning for Robust Image Classification With Noisy Labels"],"prefix":"10.1109","volume":"14","author":[{"given":"Shohei","family":"Yamamoto","sequence":"first","affiliation":[{"name":"Graduate School of Science and Engineering, Kansai University, Osaka, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0237-7461","authenticated-orcid":false,"given":"Soh","family":"Yoshida","sequence":"additional","affiliation":[{"name":"Faculty of Engineering Science, Kansai University, Osaka, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4492-5991","authenticated-orcid":false,"given":"Mitsuji","family":"Muneyasu","sequence":"additional","affiliation":[{"name":"Faculty of Engineering Science, Kansai University, Osaka, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109400"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298894"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref4","first-page":"233","article-title":"A closer look at memorization in deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"70","author":"Arpit"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.4135\/9781071810118"},{"key":"ref6","first-page":"1","article-title":"DivideMix: Learning with noisy labels as semi-supervised learning","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Li"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109013"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/WACV61041.2025.00635"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.240"},{"key":"ref10","first-page":"6226","article-title":"Peer loss functions: Learning from noisy labels without knowing noise rates","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liu"},{"key":"ref11","first-page":"14153","article-title":"Robust training under label noise by over-parameterization","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liu"},{"key":"ref12","first-page":"20331","article-title":"Early-learning regularization prevents memorization of noisy labels","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Liu"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/494"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00158"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3386829"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3680664"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.52202\/079017-1854"},{"key":"ref18","first-page":"3643","article-title":"Fine-tuning pre-trained models for robustness under noisy labels","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Ahn"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00021"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-025-02494-4"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.clsr.2013.03.010"},{"key":"ref22","volume-title":"Bill Text: AB-375 Privacy: Personal Information","author":"Legislature","year":"2017"},{"key":"ref23","first-page":"1","article-title":"The seven sins of personal-data processing systems under GDPR","volume-title":"Proc. 11th USENIX Workshop Hot Topics Cloud Comput.","author":"Shastri"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00932"},{"key":"ref25","first-page":"1","article-title":"Certified data removal from machine learning models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Guo"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25879"},{"key":"ref27","volume-title":"NeurIPS 2023 Machine Unlearning Competition","author":"Triantafillou","year":"2023"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0095"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref30","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8296803"},{"key":"ref32","first-page":"1","article-title":"Learning with symmetric label noise: The importance of being unhinged","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"van Rooyen"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3426994"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i20.35417"},{"key":"ref35","first-page":"1","article-title":"mixup: Beyond empirical risk minimization","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zhang"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01150"},{"key":"ref37","first-page":"1","article-title":"Are anchor points really indispensable in label-noise learning?","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Xia"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i20.35489"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00654"},{"key":"ref40","first-page":"1","article-title":"Learning with noisy labels revisited: A study using real-world human annotations","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wei"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298885"},{"key":"ref42","article-title":"WebVision database: Visual learning and understanding from web data","author":"Li","year":"2017","journal-title":"arXiv:1708.02862"},{"key":"ref43","first-page":"1","article-title":"Part-dependent label noise: Towards instance-dependent label noise","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Xia"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00232"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.3169\/mta.13.91"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00935"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01122"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11450351.pdf?arnumber=11450351","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T05:00:35Z","timestamp":1775192435000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11450351\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3676403","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}