{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T22:17:55Z","timestamp":1765837075613,"version":"3.48.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"38","license":[{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-025-20896-x","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T10:12:53Z","timestamp":1752833573000},"page":"47193-47204","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing the black-box transferability with Win-AdamW"],"prefix":"10.1007","volume":"84","author":[{"given":"Leiji","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxia","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5087-1910","authenticated-orcid":false,"given":"Lei","family":"Bao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"20896_CR1","unstructured":"Miltiadis K, Boris K, Yan Z et al (2024) Graph Neural Networks for Learning Equivariant Representations of Neural Networks[C]. International Conference on Learning Representations"},{"key":"20896_CR2","doi-asserted-by":"crossref","unstructured":"Kurakin A, Goodfellow IJ, Bengio S (2017) Adversarial examples in the physical world[C]. International Conference on Learning Representations, Workshop Track Proceedings","DOI":"10.1201\/9781351251389-8"},{"key":"20896_CR3","unstructured":"Szegedy C, Zaremba W, Sutskever I et al (2014) Intriguing properties of neural networks[C]. International Conference on Learning Representations"},{"key":"20896_CR4","doi-asserted-by":"publisher","first-page":"14410","DOI":"10.1109\/ACCESS.2018.2807385","volume":"6","author":"N Akhtar","year":"2018","unstructured":"Akhtar N, Mian A (2018) Threat of adversarial attacks on deep learning in computer vision: A survey[J]. IEEE Access 6:14410\u201314430","journal-title":"IEEE Access"},{"key":"20896_CR5","doi-asserted-by":"crossref","unstructured":"Papernot N, McDaniel PI, Goodfellow et al (2017) Practical Black-Box Attacks against Machine Learning[C]. In ACM on Asia Conference on Computer and Communications Security","DOI":"10.1145\/3052973.3053009"},{"key":"20896_CR6","unstructured":"Goodfellow IJ, Shlens J, Szegedy C (2015) Explaining and harnessing adversarial examples[C]. International Conference on Learning Representations"},{"key":"20896_CR7","unstructured":"Madry A, Makelov A, Schmidt L et al (2017) Towards Deep Learning Models Resistant to Adversarial Attacks. arXiv:1706.06083"},{"key":"20896_CR8","doi-asserted-by":"crossref","unstructured":"Dong YP, Liao FZ, Pang TY et al (2018) Boosting adversarial Attacks with Momentum[C]. IEEE Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR.2018.00957"},{"issue":"5","key":"20896_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/0041-5553(64)90137-5","volume":"4","author":"BT Polyak","year":"1964","unstructured":"Polyak BT (1964) Some methods of speeding up the convergence of iteration methods[J]. USSR Comput Math Math Phys 4(5):1\u201317","journal-title":"USSR Comput Math Math Phys"},{"key":"20896_CR10","unstructured":"Lin JD, Song CB, He K et al (2020) Nesterov accelerated gradient and scale invariance for adversarial attacks[C]. International Conference on Learning Representations"},{"key":"20896_CR11","first-page":"543","volume":"269","author":"Y Nesterov","year":"1983","unstructured":"Nesterov Y (1983) A method for solving the convex programming problem with convergence rate O(1\/k^2). Proc USSR Acad Sci 269:543\u2013547","journal-title":"Proc USSR Acad Sci"},{"key":"20896_CR12","first-page":"1","volume":"9983309","author":"H Yin","year":"2021","unstructured":"Yin H, Zhang H, Wang J (2021) Boosting adversarial attacks on neural networks with better optimizer[J]. Secur Communication Networks 9983309:1\u20139","journal-title":"Secur Communication Networks"},{"key":"20896_CR13","unstructured":"Zhou P, Feng JS, Ma C et al (2020) Towards theoretically understanding why SGD generalizes better than ADAM in deep learning[C]. In Advances in Neural Information Processing Systems"},{"key":"20896_CR14","unstructured":"Zhou P, Xiong C, Socher R et al (2020) Theory-inspired path regularized differential network architecture search[C]. In Advances in Neural Information Processing Systems"},{"key":"20896_CR15","unstructured":"Loshchilov I, Hutter F (2017) Decoupled weight decay regularization. arXiv:1711.05101"},{"key":"20896_CR16","unstructured":"Touvron H, Cord M, Douze M et al (2021) Training data-efficient image transformers & distillation through attention[C]. International Conference on Machine Learning"},{"key":"20896_CR17","unstructured":"Zhou P, Xie XY, Yan SC (2023) Win: weight-decay-integrated Nesterov acceleration for adaptive gradient algorithms[C]. In International Conference on Learning Representations"},{"key":"20896_CR18","doi-asserted-by":"crossref","unstructured":"Nesterov Y (2018) Lectures on convex optimization[M], vol 137. Springer","DOI":"10.1007\/978-3-319-91578-4_2"},{"key":"20896_CR19","unstructured":"Combettes PL, Wajs V (2005) An introduction to modern convex Analysis[M]. Cambridge University Press"},{"key":"20896_CR20","unstructured":"Rebuffi SA, Gowal S, Calian DA et al (2021) Data augmentation can improve robustness[C]. Advances in Neural Information Processing Systems"},{"key":"20896_CR21","doi-asserted-by":"crossref","unstructured":"Xie CH, Zhang ZS, Wang JY et al (2019) Improving transferability of adversarial examples with input diversity[C]. IEEE Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR.2019.00284"},{"key":"20896_CR22","doi-asserted-by":"crossref","unstructured":"Dong YP, Pang TY, Su H et al (2019) Evading defenses to transferable adversarial examples by translation-invariant attacks[C]. IEEE Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR.2019.00444"},{"key":"20896_CR23","unstructured":"Ashia CW, Rebecca R, Mitchell S et al (2017) The marginal value of adaptive gradient methods in machine learning[C]. Advances in neural information processing systems"},{"key":"20896_CR24","unstructured":"Zachary N, Justin MG, Christopher JS et al (2021) A large batch optimizer reality check: traditional, generic optimizers suffice across batch sizes. arXiv:2102.06356"},{"key":"20896_CR25","unstructured":"Kim JL, Toulis P, Kyrillidis A (2022) Convergence and stability of the stochastic proximal point algorithm with momentum[C]. Proceedings of Machine Learning Research"},{"key":"20896_CR26","first-page":"27290","volume":"34","author":"P Zhou","year":"2021","unstructured":"Zhou P, Yan HS, Yuan XT et al (2021) Towards Understanding why Lookahead generalizes better than SGD and beyond[C]. Adv Neural Inf Process Syst 34:27290\u201327304","journal-title":"Adv Neural Inf Process Syst"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-025-20896-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-025-20896-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-025-20896-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T22:13:52Z","timestamp":1765836832000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-025-20896-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,18]]},"references-count":26,"journal-issue":{"issue":"38","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["20896"],"URL":"https:\/\/doi.org\/10.1007\/s11042-025-20896-x","relation":{},"ISSN":["1573-7721"],"issn-type":[{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2025,7,18]]},"assertion":[{"value":"17 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 April 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"I would like to submit the manuscript entitled \u201cEnhancing the Transferability with Win-AdamW\u201d to be considered for publication as an original article in the Multimedia Tools and Applications. We declare that this manuscript is original, has not been published before.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that there are no conflicts of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}