{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:20:31Z","timestamp":1776183631873,"version":"3.50.1"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:00:00Z","timestamp":1702598400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:00:00Z","timestamp":1702598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100005047","name":"Natural Science Foundation of Liaoning Province","doi-asserted-by":"publisher","award":["2022-MS-353"],"award-info":[{"award-number":["2022-MS-353"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Scientific Research Project of Education Department of Liaoning Province","award":["LJKMZ20220640"],"award-info":[{"award-number":["LJKMZ20220640"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s13042-023-02028-9","type":"journal-article","created":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T13:02:08Z","timestamp":1702645328000},"page":"2283-2296","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Simpler large margin distribution machine via weighted linear loss for large-scale classification"],"prefix":"10.1007","volume":"15","author":[{"given":"Maoxiang","family":"Chu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liming","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongfen","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,15]]},"reference":[{"issue":"3","key":"2028_CR1","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273\u2013297","journal-title":"Mach Learn"},{"key":"2028_CR2","first-page":"75","volume":"2018","author":"RF de Mello","year":"2018","unstructured":"de Mello RF, Ponti MA (2018) Statistical learning theory. Mach Learn 2018:75\u2013128","journal-title":"Mach Learn"},{"issue":"10","key":"2028_CR3","doi-asserted-by":"publisher","first-page":"7253","DOI":"10.1109\/TPAMI.2021.3092177","volume":"44","author":"H Wang","year":"2022","unstructured":"Wang H, Shao Y, Zhou S, Zhang C, Xiu N (2022) Support vector machine classifier via L0\/1 soft-margin loss. IEEE Trans Pattern Anal Mach Intell 44(10):7253\u20137265","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"2028_CR4","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1109\/TNNLS.2021.3097248","volume":"34","author":"B Gu","year":"2021","unstructured":"Gu B, Xiong Z, Li X, Zhai Z, Zheng G (2021) Kernel path for \u03bd-support vector classification. IEEE Trans Neural Netw Learn Syst 34(1):490\u2013501","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"10","key":"2028_CR5","doi-asserted-by":"publisher","first-page":"6184","DOI":"10.1109\/TPAMI.2021.3085969","volume":"44","author":"Z Akram-Ali-Hammouri","year":"2022","unstructured":"Akram-Ali-Hammouri Z, Fernandez-Delgado M, Cernadas E, Barro S (2022) Fast support vector classification for large-scale problems. IEEE Trans Pattern Anal Mach Intell 44(10):6184\u20136195","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"2028_CR6","doi-asserted-by":"publisher","first-page":"3235","DOI":"10.1007\/s13042-020-01248-7","volume":"12","author":"DN Le","year":"2021","unstructured":"Le DN, Parvathy VS, Gupta D, Khanna A, Rodrigues Joel JPC, Shankar K (2021) IoT enabled depthwise separable convolution neural network with deep support vector machine for COVID-19 diagnosis and classification. Int J Mach Learn Cybern 12(11):3235\u20133248","journal-title":"Int J Mach Learn Cybern"},{"key":"2028_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2021.102983","volume":"178","author":"M Mokhtar","year":"2021","unstructured":"Mokhtar M, Tarik AR, Sarkhel HTK, Adil HMA, Quan TT, Moazam B, Amir MR, Mehdi H (2021) A comprehensive survey and taxonomy of the SVM-based intrusion detection systems. J Netw Comput Appl 178:102983","journal-title":"J Netw Comput Appl"},{"key":"2028_CR8","doi-asserted-by":"publisher","first-page":"3069","DOI":"10.1007\/s00366-021-01299-6","volume":"38","author":"T Cuong-Le","year":"2022","unstructured":"Cuong-Le T, Nghia-Nguyen T, Khatir S, Trong-Nguyen P, Mirjalili S, Nguyen KD (2022) An efficient approach for damage identification based on improved machine learning using PSO-SVM. Eng Comput 38:3069\u20133084","journal-title":"Eng Comput"},{"key":"2028_CR9","doi-asserted-by":"crossref","unstructured":"Li B, Wang Q, Hu J (2009) A fast SVM training method for very large datasets. In: Proceedings of 2009 international joint conference on neural networks, Atlanta, pp 1784\u20131789","DOI":"10.1109\/IJCNN.2009.5178618"},{"issue":"5","key":"2028_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.artint.2013.07.002","volume":"203","author":"W Gao","year":"2013","unstructured":"Gao W, Zhou ZH (2013) On the doubt about margin explanation of boosting. Artif Intell 203(5):1\u201318","journal-title":"Artif Intell"},{"issue":"7","key":"2028_CR11","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.1162\/089976699300016106","volume":"11","author":"L Breiman","year":"1999","unstructured":"Breiman L (1999) Prediction games and arcing classifers. Neural Comput 11(7):1493\u20131517","journal-title":"Neural Comput"},{"key":"2028_CR12","doi-asserted-by":"crossref","unstructured":"Zhang T, Zhou ZH (2014) Large margin distribution machine. In: Proceedings of ACM SIGKDD international conference on knowledge discovery and data mining, vol 20. ACM, pp 313\u2013322","DOI":"10.1145\/2623330.2623710"},{"issue":"6","key":"2028_CR13","doi-asserted-by":"publisher","first-page":"1143","DOI":"10.1109\/TKDE.2019.2897662","volume":"32","author":"T Zhang","year":"2019","unstructured":"Zhang T, Zhou ZH (2019) Optimal margin distribution machine. IEEE Trans Knowl Data Eng 32(6):1143\u20131156","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2028_CR14","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.patrec.2017.01.010","volume":"88","author":"F Cheng","year":"2017","unstructured":"Cheng F, Zhang J, Li Z, Tang M (2017) Double distribution support vector machine. Pattern Recognit Lett 88:20\u201325","journal-title":"Pattern Recognit Lett"},{"key":"2028_CR15","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.neucom.2016.10.053","volume":"224","author":"F Cheng","year":"2017","unstructured":"Cheng F, Zhang J, Wen C, Liu Z, Li Z (2017) Large cost-sensitive margin distribution machine for imbalanced data classifcation. Neurocomputing 224:45\u201357","journal-title":"Neurocomputing"},{"key":"2028_CR16","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","author":"J Suykens","year":"1999","unstructured":"Suykens J, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9:293\u2013300","journal-title":"Neural Process Lett"},{"key":"2028_CR17","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1016\/j.procs.2014.05.311","volume":"31","author":"YH Shao","year":"2014","unstructured":"Shao YH, Wang Z, Yang ZM, Deng NY (2014) Weighted linear loss support vector machine for large scale problems. Proc Comput Sci 31:639\u2013647","journal-title":"Proc Comput Sci"},{"key":"2028_CR18","doi-asserted-by":"publisher","DOI":"10.1201\/b14297","volume-title":"Support vector machines optimization based theory, algorithms and extensions","author":"N Deng","year":"2012","unstructured":"Deng N, Tian Y, Zhang C (2012) Support vector machines optimization based theory, algorithms and extensions. Chapman and Hall\/\/CRC, London"},{"key":"2028_CR19","unstructured":"Dua D, Taniskidou EK. UCI machine learning repository [Online]. http:\/\/archive.ics.uci.edu\/ml\/"},{"key":"2028_CR20","unstructured":"Musicant DR (1998) NDC: normally distributed clustered datasets. http:\/\/www.cs.wisc.edu\/dmi\/svm\/ndc\/"},{"key":"2028_CR21","first-page":"1","volume":"70","author":"Y Bao","year":"2021","unstructured":"Bao Y, Song K, Liu J, Wang Y, Yan Y, Yu H, Li X (2021) Triplet-graph reasoning network for few-shot metal generic surface defect segmentation. IEEE Trans Instrum Meas 70:1\u201311","journal-title":"IEEE Trans Instrum Meas"},{"issue":"4","key":"2028_CR22","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.1109\/TIM.2019.2915404","volume":"69","author":"Y He","year":"2019","unstructured":"He Y, Song K, Meng Q, Yan Y (2019) An end-to-end steel surface defect detection approach via fusing multiple hierarchical features. IEEE Trans Instrum Meas 69(4):1493\u20131504","journal-title":"IEEE Trans Instrum Meas"},{"key":"2028_CR23","doi-asserted-by":"publisher","first-page":"13341","DOI":"10.1007\/s11042-022-13738-7","volume":"82","author":"BB Hazarika","year":"2023","unstructured":"Hazarika BB, Gupta D (2023) Improved twin bounded large margin distribution machines for binary classification. Multimed Tools Appl 82:13341\u201313368","journal-title":"Multimed Tools Appl"},{"key":"2028_CR24","unstructured":"The Math Works (MATLAB 2016b), Inc. [Online]. http:\/\/www.mathworks.com"},{"key":"2028_CR25","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J (2006) Statistical comparisons of classifers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"key":"2028_CR26","unstructured":"Nemenyi P (1963) Distribution-free multiple comparisons. https:\/\/books.google.f\/books?id=nhDMtgAACAAJ"},{"issue":"1","key":"2028_CR27","first-page":"1","volume":"9","author":"AK Nain","year":"2016","unstructured":"Nain AK, Gupta S, Bhushan B (2016) An extension to switching bilateral filter for mixed noise removal from colour image. Int J Signal Imaging 9(1):1\u201319","journal-title":"Int J Signal Imaging"},{"key":"2028_CR28","doi-asserted-by":"crossref","unstructured":"Yuan L, Yu Q, Shen C, Hu W, Yang Z (2016) New Watershed segmentation algorithm based on hybrid gradient and self-adaptive marker extraction. In: Proceedings of 2016 2nd IEEE international conference on computer and communications (ICCC). IEEE, pp 624\u2013628","DOI":"10.1109\/CompComm.2016.7924776"},{"key":"2028_CR29","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.neucom.2015.05.134","volume":"181","author":"H Hu","year":"2016","unstructured":"Hu H, Liu Y, Liu M, Nie L (2016) Surface defect classification in large-scale strip steel image collection via hybrid chromosome genetic algorithm. Neurocomputing 181:86\u201395","journal-title":"Neurocomputing"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-02028-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-023-02028-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-02028-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,23]],"date-time":"2024-05-23T05:29:54Z","timestamp":1716442194000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-023-02028-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,15]]},"references-count":29,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["2028"],"URL":"https:\/\/doi.org\/10.1007\/s13042-023-02028-9","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,15]]},"assertion":[{"value":"31 January 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 December 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}