{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,29]],"date-time":"2025-03-29T05:10:10Z","timestamp":1743225010172,"version":"3.40.3"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Shaanxi Key Research and Development Program","award":["2024QY2-GJHX-05"],"award-info":[{"award-number":["2024QY2-GJHX-05"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1109\/tetci.2025.3540419","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T18:52:51Z","timestamp":1740163971000},"page":"1490-1501","source":"Crossref","is-referenced-by-count":0,"title":["A Tunable Framework for Joint Trade-Off Between Accuracy and Multi-Norm Robustness"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2017-962X","authenticated-orcid":false,"given":"Haonan","family":"Zheng","sequence":"first","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8181-7001","authenticated-orcid":false,"given":"Xinyang","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5429-2748","authenticated-orcid":false,"given":"Wen","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2020.3041019"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3233042"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2024.3368964"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2019.2960546"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2017.2784878"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3430080"},{"key":"ref8","article-title":"Intriguing properties of neural networks","volume-title":"Proc. 2nd Int. Conf. Learn. Representations","author":"Szegedy","year":"2014"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681184"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3686835"},{"key":"ref11","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Goodfellow","year":"2015"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01712"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i1.27788"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3002587"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3151315"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2020.2968933"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2019.2961157"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2022.3201294"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.06083"},{"key":"ref21","first-page":"7472","article-title":"Theoretically principled trade-off between robustness and accuracy","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhang","year":"2019"},{"key":"ref22","first-page":"2958","article-title":"Adversarial weight perturbation helps robust generalization","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Wu","year":"2020"},{"key":"ref23","first-page":"5866","article-title":"Adversarial training and robustness for multiple perturbations","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","author":"Tramer","year":"2019"},{"key":"ref24","article-title":"Improving adversarial robustness requires revisiting misclassified examples","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Wang","year":"2020"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01304"},{"key":"ref26","first-page":"4436","article-title":"Adversarial robustness against multiple and single lp-threat models via quick fine-tuning of robust classifiers","volume-title":"Proc. 39th Int. Conf. Mach. Learn.","author":"Croce","year":"2022"},{"article-title":"Adversarial logit pairing","year":"2018","author":"Kannan","key":"ref27"},{"key":"ref28","first-page":"7449","article-title":"Once-for-all adversarial training: In-situ tradeoff between robustness and accuracy for free","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Wang","year":"2020"},{"key":"ref29","first-page":"6640","article-title":"Adversarial robustness against the union of multiple perturbation models","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","author":"Maini","year":"2020"},{"key":"ref30","first-page":"7279","article-title":"Learning to generate noise for multi-attack robustness","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","author":"Madaan","year":"2021"},{"key":"ref31","first-page":"25870","article-title":"Toward efficient robust training against union of lp threat models","volume-title":"Proc. 36th Int. Conf. Neural Informat. Process. Syst","author":"Sriramanan","year":"2022"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00090"},{"issue":"3","key":"ref33","first-page":"8405","article-title":"One pixel attack for fooling neural networks","volume":"25","author":"Sinha","year":"2021","journal-title":"Ann. Romanian Soc. Cell Biol."},{"key":"ref34","first-page":"2507","article-title":"LaVAN: Localized and visible adversarial noise","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","author":"Karmon","year":"2018"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19772-7_31"},{"key":"ref36","first-page":"2206","article-title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","author":"Croce","year":"2020"},{"key":"ref37","first-page":"2201","article-title":"Mind the Box: l1-APGD for sparse adversarial attacks on image classifiers","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","author":"Croce","year":"2021"},{"key":"ref38","first-page":"272","article-title":"Efficient projections onto the l1-ball for learning in high dimensions","volume-title":"Proc. 25th Int. Conf. Mach. Learn.","author":"Duchi","year":"2008"},{"key":"ref39","article-title":"MMA training: Direct input space margin maximization through adversarial training","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Ding","year":"2020"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref41","first-page":"87.1","article-title":"Wide residual networks","volume-title":"Proc. Brit. Mach. Vis. Conf.","author":"Zagoruyko","year":"2016"},{"article-title":"Learning Multiple Layers of Features From Tiny Images","year":"2009","author":"Krizhevsky","key":"ref42"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00068"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3455008"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00238"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/T-C.1974.223784"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.2118\/18761-MS"}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7433297\/10939044\/10897885.pdf?arnumber=10897885","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,29]],"date-time":"2025-03-29T04:30:00Z","timestamp":1743222600000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10897885\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":47,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2025.3540419","relation":{},"ISSN":["2471-285X"],"issn-type":[{"type":"electronic","value":"2471-285X"}],"subject":[],"published":{"date-parts":[[2025,4]]}}}