{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T15:55:03Z","timestamp":1777478103682,"version":"3.51.4"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2018,10,29]],"date-time":"2018-10-29T00:00:00Z","timestamp":1540771200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Qiaolin Ye","award":["61871444"],"award-info":[{"award-number":["61871444"]}]},{"name":"Fuquan Zhang","award":["31670554"],"award-info":[{"award-number":["31670554"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s13042-018-0881-y","type":"journal-article","created":{"date-parts":[[2018,10,29]],"date-time":"2018-10-29T09:39:08Z","timestamp":1540805948000},"page":"2449-2457","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Infinite norm large margin classifier"],"prefix":"10.1007","volume":"10","author":[{"given":"Hongxin","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5504-8392","authenticated-orcid":false,"given":"Xubing","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuquan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaolin","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xijian","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,29]]},"reference":[{"key":"881_CR1","doi-asserted-by":"publisher","DOI":"10.1177\/1362361318766247","author":"K Campbell","year":"2018","unstructured":"Campbell K, Carpenter KL, Hashemi J, Espinosa S, Marsan S, Borg JS et al (2018) Computer vision analysis captures atypical attention in toddlers with autism. Autism. \n                    https:\/\/doi.org\/10.1177\/1362361318766247","journal-title":"Autism"},{"issue":"9","key":"881_CR2","doi-asserted-by":"publisher","first-page":"902","DOI":"10.1007\/s11263-018-1073-7","volume":"126","author":"M M\u00fcller","year":"2018","unstructured":"M\u00fcller M, Casser V, Lahoud J, Smith N, Ghanem B (2018) Sim4CV: a photo-realistic simulator for computer vision applications. Int J Comput Vis 126(9):902\u2013919","journal-title":"Int J Comput Vis"},{"key":"881_CR3","doi-asserted-by":"crossref","unstructured":"Wegner JD, Tuia D, Yang M et al (2018) Foreword to the theme issue on geospatial computer vision","DOI":"10.1016\/j.isprsjprs.2017.12.011"},{"key":"881_CR4","doi-asserted-by":"publisher","DOI":"10.1201\/9780429499661","volume-title":"Introduction to the theory of neural computation","author":"JA Hertz","year":"2018","unstructured":"Hertz JA (2018) Introduction to the theory of neural computation. CRC Press, Boca Raton"},{"issue":"4","key":"881_CR5","doi-asserted-by":"publisher","first-page":"899","DOI":"10.1109\/TNN.2005.849821","volume":"16","author":"C Domeniconi","year":"2005","unstructured":"Domeniconi C, Gunopulos D, Peng J (2005) Large margin nearest neighbor classifiers. IEEE Trans Neural Netw 16(4):899\u2013909","journal-title":"IEEE Trans Neural Netw"},{"issue":"2","key":"881_CR6","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/TNN.2007.905855","volume":"19","author":"K Huang","year":"2008","unstructured":"Huang K, Yang H, King I et al (2008) Maxi\u2013min margin machine: learning large margin classifiers locally and globally. IEEE Trans Neural Netw 19(2):260\u2013272","journal-title":"IEEE Trans Neural Netw"},{"issue":"2","key":"881_CR7","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s10994-007-5015-9","volume":"68","author":"DS Yeung","year":"2007","unstructured":"Yeung DS, Wang D, Ng WWY et al (2007) Structured large margin machines: sensitive to data distributions. Mach Learn 68(2):171\u2013200","journal-title":"Mach Learn"},{"key":"881_CR8","unstructured":"Lanckriet G, Ghaoui LE, Bhattacharyya C et al (2002) Minimax probability machine\/\/Advances in neural information processing systems. 801\u2013807"},{"issue":"3","key":"881_CR9","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","author":"JAK Suykens","year":"1999","unstructured":"Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293\u2013300","journal-title":"Neural Process Lett"},{"issue":"1\u20132","key":"881_CR10","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/s10994-005-0463-6","volume":"59","author":"GM Fung","year":"2005","unstructured":"Fung GM, Mangasarian OL (2005) Multicategory proximal support vector machine classifiers. Mach Learning 59(1\u20132):77\u201397","journal-title":"Mach Learning"},{"issue":"1","key":"881_CR11","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1109\/TPAMI.2006.17","volume":"28","author":"OL Mangasarian","year":"2006","unstructured":"Mangasarian OL, Wild EW (2006) Multisurface proximal support vector machine classification via generalized eigenvalues. IEEE Trans Pattern Anal Mach Intell 28(1):69\u201374","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"881_CR12","unstructured":"Lopez J, De Brabanter K, Dorronsoro JR et al (2011) Sparse LSSVMs with L0-norm minimization\/\/Proc Eur Symp Artif Neural Netw, Comput Intell Mach Learn, pp\u00a0189\u2013194"},{"key":"881_CR13","volume-title":"1-norm support vector machines","author":"J Zhu","year":"2003","unstructured":"Zhu J, Rosset S, Hastie T, Tibshirani R (2003) 1-norm support vector machines. Adv Neural Inf Process Syst (NIPS 2003), Vancouver, British Columbia, Canda"},{"key":"881_CR14","unstructured":"Blanco V, Puerto J, Rodr\u00edguez-Ch\u00eda AM (2017) On LP-support vector machines and multidimensional kernels. arXiv:1711.10332"},{"key":"881_CR15","first-page":"379","volume":"18","author":"H Zou","year":"2008","unstructured":"Zou H, Yuan M (2008) The F\u221e-norm support vector machine. Stat Sin 18:379\u2013398","journal-title":"Stat Sin"},{"key":"881_CR16","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1016\/j.patcog.2017.09.035","volume":"74","author":"H Yan","year":"2018","unstructured":"Yan H, Ye Q, Yu DJ et al (2018) Least squares twin bounded support vector machines based on L1-norm distance metric for classification. Pattern Recogn 74:434\u2013447","journal-title":"Pattern Recogn"},{"key":"881_CR17","doi-asserted-by":"crossref","unstructured":"Rusu C, Gonzalez-Prelcic N, Heath RW Jr (2018) Algorithms for the construction of incoherent frames under various design constraints. arXiv:1801.09678","DOI":"10.1016\/j.sigpro.2018.06.015"},{"key":"881_CR18","unstructured":"Egolf D, Chee R, Chowdhury G et al (2018) Super-resolution photoacoustic imaging of sparse absorbers using L1-norm minimization (Conference Presentation)\/\/Photons Plus Ultrasound: Imaging and Sensing 2018. International Society for Optics and Photonics, pp\u00a010494"},{"key":"881_CR19","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.eswa.2017.12.014","volume":"97","author":"S Lee","year":"2018","unstructured":"Lee S, Jun CH (2018) Fast incremental learning of logistic model tree using least angle regression. Expert Syst Appl 97:137\u2013145","journal-title":"Expert Syst Appl"},{"issue":"1","key":"881_CR20","doi-asserted-by":"publisher","first-page":"465","DOI":"10.3150\/16-BEJ885","volume":"24","author":"JM Aza\u00efs","year":"2018","unstructured":"Aza\u00efs JM, De Castro Y, Mourareau S (2018) Power of the spacing test for least-angle regression. Bernoulli 24(1):465\u2013492","journal-title":"Bernoulli"},{"issue":"1\u20132","key":"881_CR21","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/S0167-6377(98)00049-2","volume":"24","author":"OL Mangasarian","year":"1999","unstructured":"Mangasarian OL (1999) Arbitrary-norm separating planefn1. Oper Res Lett 24(1\u20132):15\u201323","journal-title":"Oper Res Lett"},{"key":"881_CR22","volume-title":"Proceedings of a symposium conducted by the Mathematics Research Center, The University of Wisconsin, Madison, May 4\u20136, 1970","author":"Nonlinear Programming","year":"2014","unstructured":"Nonlinear Programming (2014) Proceedings of a symposium conducted by the Mathematics Research Center, The University of Wisconsin, Madison, May 4\u20136, 1970. Elsevier, New York"},{"issue":"02","key":"881_CR23","first-page":"133","volume":"49","author":"X Yang","year":"2013","unstructured":"Yang X.,Wang Y, Chen, Bin (2013) Study on several key problems in Mahalanobis measure learning and Geometric explanation. J Nanjing Univ (Nat Sci) 49(02):133\u2013141 (In Chinese with English Abstract)","journal-title":"J Nanjing Univ (Nat Sci)"},{"key":"881_CR24","unstructured":"Blake C, Keogh E, Merz CJ (1998) UCI repository of machine learning databases. Department of Information and Computer Science, University of California, Irvine. \n                    http:\/\/www.ics.uci.edu\/~mlearn\/MLRepository.html"},{"issue":"1","key":"881_CR25","first-page":"e005499","volume":"11","author":"MM Kalscheur","year":"2018","unstructured":"Kalscheur MM, Kipp RT, Tattersall MC et al (2018) Machine learning algorithm predicts cardiac resynchronization therapy outcomes: lessons from the COMPANION trial. Circulation 11(1):e005499","journal-title":"Circulation"},{"issue":"1","key":"881_CR26","doi-asserted-by":"publisher","first-page":"3","DOI":"10.2174\/1574893611666160608075753","volume":"13","author":"SP Wang","year":"2018","unstructured":"Wang SP, Zhang Q, Lu J et al (2018) Analysis and prediction of nitrated tyrosine sites with the mRMR method and support vector machine algorithm. Curr Bioinform 13(1):3\u201313","journal-title":"Curr Bioinform"},{"key":"881_CR27","unstructured":"Blanco V, Puerto J, Rodr\u00edguez-Ch\u00eda AM (2017) On LP-support vector machines and multi- dimensional Kernels. arXiv:1711.10332"},{"key":"881_CR28","unstructured":"Chen J (2010) Convex relaxations in nonconvex and applied optimization. PhD thesis, University of Iowa. \n                    http:\/\/ir.uiowa.edu\/etd\/654"},{"key":"881_CR29","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/j.measurement.2018.01.036","volume":"118","author":"T Han","year":"2018","unstructured":"Han T, Jiang D, Sun Y et al (2018) Intelligent fault diagnosis method for rotating machinery via dictionary learning and sparse representation-based classification. Measurement 118:181\u2013193","journal-title":"Measurement"},{"issue":"3","key":"881_CR30","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1007\/s13042-016-0544-9","volume":"9","author":"X Luo","year":"2018","unstructured":"Luo X, Yang X, Jiang C et al (2018) Timeliness online regularized extreme learning machine. Int J Mach Learn Cybernet 9(3):465\u2013476","journal-title":"Int J Mach Learn Cybernet"},{"issue":"8","key":"881_CR31","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1007\/s00500-017-2505-y","volume":"22","author":"X Ma","year":"2018","unstructured":"Ma X, Liu S, Hu S et al (2018) SAR image edge detection via sparse representation. Soft Comput 22(8):2507\u20132515","journal-title":"Soft Comput"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0881-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-018-0881-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0881-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,28]],"date-time":"2019-10-28T20:16:53Z","timestamp":1572293813000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-018-0881-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,29]]},"references-count":31,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["881"],"URL":"https:\/\/doi.org\/10.1007\/s13042-018-0881-y","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,29]]},"assertion":[{"value":"11 April 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 October 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 October 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}