{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T20:22:55Z","timestamp":1772050975414,"version":"3.50.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1007\/s11063-020-10353-1","type":"journal-article","created":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T10:02:41Z","timestamp":1600855361000},"page":"2371-2397","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Robust Least Squares Support Vector Machine Based on L\u221e-norm"],"prefix":"10.1007","volume":"52","author":[{"given":"Ting","family":"Ke","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lidong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuechun","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,23]]},"reference":[{"key":"10353_CR1","first-page":"273","volume":"20","author":"Vapnik VN Cortes","year":"1995","unstructured":"Cortes Vapnik VN (1995) Support vector networks. Mach Learn 20:273\u2013297","journal-title":"Mach Learn"},{"key":"10353_CR2","volume-title":"Statistical learning theory","author":"VN Vapnik","year":"1998","unstructured":"Vapnik VN (1998) Statistical learning theory. Wiley, New York"},{"key":"10353_CR3","unstructured":"Boser BE, Guyon IM, Vapnik VN (1996) A training algorithm for optimal margin classifiers. In: Proceedings of annual Acm workshop on computational learning theory, pp 144\u2013152"},{"key":"10353_CR4","first-page":"137","volume-title":"European conference on machine learning","author":"T Joachims","year":"1998","unstructured":"Joachims T, Ndellec C, Rouveriol (1998) Text categorization with support vector machines: learning with many relevant features. European conference on machine learning. Chemnitz, Germany, pp 137\u2013142"},{"key":"10353_CR5","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.neucom.2015.10.139","volume":"211","author":"Q Tao","year":"2016","unstructured":"Tao Q, Zhan S, Li XH, Kurihara T (2016) Robust\u00a0face detection\u00a0using local CNN and SVM based on kernel combination. Nurocomputing 211:98\u2013105","journal-title":"Nurocomputing"},{"key":"10353_CR6","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1023\/A:1012487302797","volume":"46","author":"I Guyon","year":"2002","unstructured":"Guyon I, Weston J, Barnhill S, Vapnik VN (2002) Gene selection for cancer classification using support vector machine. Mach Learn 46:389\u2013422","journal-title":"Mach Learn"},{"key":"10353_CR7","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1016\/j.neucom.2004.12.006","volume":"67","author":"S Chen","year":"2005","unstructured":"Chen S, Wang M (2005) Seeking multi-threshold directly from support vectors for image segmentation. Neurocomputing 67:335\u2013344","journal-title":"Neurocomputing"},{"issue":"4","key":"10353_CR8","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1623\/hysj.51.4.599","volume":"51","author":"JY Lin","year":"2006","unstructured":"Lin JY, Cheng CT, Chau KW (2006) Using support vector machines for long-term discharge prediction. Hydrol Sci J 51(4):599\u2013612","journal-title":"Hydrol Sci J"},{"key":"10353_CR9","first-page":"243","volume-title":"Advances in kernel methods-Support Vector Learning","author":"Smola AJ MullerKR","year":"1999","unstructured":"MullerKR Smola AJ, Ratsch G, Sch\u00f6lkopf B, Kohlmorgen J (1999) Using support vector machines for time series prediction. Advances in kernel methods-Support Vector Learning. MIT Press, Cambridge, pp 243\u2013254"},{"key":"10353_CR10","unstructured":"Platt JC (1999) Fast training of support vector machines using sequential minimal optimization. In: Advances in kernel methods, pp 185\u2013208"},{"key":"10353_CR11","unstructured":"Joachims T (1999) Making large-scale support vector machine learning practical. In: Advances in kernel methods, pp 169\u2013184"},{"issue":"3","key":"10353_CR12","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang CC, Lin CJ (2011) Libsvm: a library for support vector machines. ACM Trans Intell Syst Technol 2(3):389\u2013396","journal-title":"ACM Trans Intell Syst Technol"},{"issue":"3","key":"10353_CR13","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":"10353_CR14","first-page":"29","volume":"10","author":"JAK Suykens","year":"2000","unstructured":"Suykens JAK (2000) Least squares support vector machines for classification and nonlinear modeling. Neural Network World 10(1\u20132):29\u201347","journal-title":"Neural Network World"},{"key":"10353_CR15","doi-asserted-by":"publisher","DOI":"10.1142\/5089","volume-title":"Least squares support vector machines","author":"JAK Suykens","year":"2002","unstructured":"Suykens JAK, Gestel TV, Brabanter JD, Moor BD, Vandewalle J (2002) Least squares support vector machines. World Scientific, Singapore"},{"issue":"3","key":"10353_CR16","first-page":"22","volume":"263","author":"YH Shao","year":"2014","unstructured":"Shao YH, Chen WJ, Deng NY (2014) Nonparallel hyperplane support vector machine for binary classification problems. Inf Sci Int J 263(3):22\u201335","journal-title":"Inf Sci Int J"},{"issue":"5","key":"10353_CR17","doi-asserted-by":"publisher","first-page":"1086","DOI":"10.1109\/TNNLS.2014.2333879","volume":"26","author":"R Mall","year":"2015","unstructured":"Mall R, Suykens J (2015) Very sparse LSSVM reductions for large-scale data. IEEE Trans Neural Netw Learn Syst 26(5):1086\u20131097","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10353_CR18","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.patcog.2016.02.012","volume":"59","author":"Y Gao","year":"2016","unstructured":"Gao Y, Shan X, Hu Z et al (2016) Extended compressed tracking via random projection based on MSERs and online LS-SVM learning. Pattern Recognit 59:245\u2013254","journal-title":"Pattern Recognit"},{"issue":"6","key":"10353_CR19","doi-asserted-by":"publisher","first-page":"1494","DOI":"10.4304\/jsw.9.6.1494-1502","volume":"9","author":"T Ke","year":"2014","unstructured":"Ke T, Song LJ, Yang B, Zhao XB, Jing L (2014) Building a biased least squares support vector machine classifier for positive and unlabeled learning. J Softw 9(6):1494\u20131502","journal-title":"J Softw"},{"key":"10353_CR20","unstructured":"Lopez J, Brabanter KD, Dorronsoro JR, et al (2011) Sparse LSSVMs with L0-Norm minimization. In: Proceedings of the European symposium on artificial neural networks, computational intelligence and machine learning (ESANN 2011), pp 189\u2013194"},{"key":"10353_CR21","unstructured":"Drucker H, Burges CJC, Kaufman L, Smola A, Vapnik VN (1997) Support vector regression machines. Bell Labs and Monmouth University"},{"key":"10353_CR22","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.patcog.2018.01.016","volume":"78","author":"YH Shao","year":"2018","unstructured":"Shao YH, Li CN, Liu MZ, Wang Z, Deng NY (2018) Sparse Lq-norm least squares support vector machine with feature selection. Pattern Recognt 78:167\u2013181","journal-title":"Pattern Recognt"},{"key":"10353_CR23","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1007\/s11668-016-0140-z","volume":"16","author":"Z Chiremsel","year":"2016","unstructured":"Chiremsel Z, Nait SR, Chiremsel R (2016) Probabilistic fault diagnosis of Safety instrumented systems based on fault tree analysis and Bayesian network. J Fail Anal Preven 16:747\u2013760","journal-title":"J Fail Anal Preven"},{"key":"10353_CR24","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.ins.2020.03.021","volume":"523","author":"HJ Ju","year":"2020","unstructured":"Ju HJ, Lee DH, Hwang JY, Namkung JY, Yu H (2020) PUMAD: PU metric learning for anomaly detection. Inf Sci 523:167\u2013183","journal-title":"Inf Sci"},{"issue":"9","key":"10353_CR25","doi-asserted-by":"publisher","first-page":"1672","DOI":"10.1109\/TPAMI.2008.114","volume":"30","author":"N Kwak","year":"2008","unstructured":"Kwak N (2008) Principal component analysis based on l1-norm maximization. IEEE Trans Pattern Anal Mach Intell 30(9):1672\u20131680","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"10353_CR26","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1037\/0033-295X.93.2.136","volume":"93","author":"D Kahneman","year":"1986","unstructured":"Kahneman D, Miller Dale T (1986) Norm theory: comparing reality to its alternatives. Psychol Rev 93(2):136\u2013153","journal-title":"Psychol Rev"},{"key":"10353_CR27","unstructured":"John C, Platt (1998) Sequential Minimal Optimization: a fast algorithm for training Support Vector Machines. [D]"},{"key":"10353_CR28","doi-asserted-by":"crossref","unstructured":"Osuna E, Freund R, Girosi, F (1997) Improved training algorithm for support vector machines. In: Proceedings of IEEE NNSP\u201997, pp 1\u201310","DOI":"10.1109\/NNSP.1997.622408"},{"key":"10353_CR29","unstructured":"Lin ZR (2016) LIBSVM http:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvm"},{"key":"10353_CR30","unstructured":"Pelckmans K, Suykens JAK, Gestel TV, et al (2002) LS-SVM lab: a matlab tool-box for least squares support vector machines. In: Tutorial KU Leuven-ESAT Leuven, Belgium, pp 1\u20132"},{"key":"10353_CR31","doi-asserted-by":"crossref","unstructured":"Tian YJ, Yu J, Chen WJ (2010) Lp-Norm Support Vector Machine with CCCP. In: Proceedings of seventh international conference on fuzzy systems and knowledge discovery, pp 1560\u20131564","DOI":"10.1109\/FSKD.2010.5569345"},{"key":"10353_CR32","unstructured":"Blake CL, Merz CJ (1998) UCI Repository for machine learning databases: http:\/\/archive.ics.uci.edu\/ml\/datasets.php"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-020-10353-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-020-10353-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-020-10353-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,23]],"date-time":"2021-09-23T00:50:04Z","timestamp":1632358204000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-020-10353-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,23]]},"references-count":32,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["10353"],"URL":"https:\/\/doi.org\/10.1007\/s11063-020-10353-1","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,23]]},"assertion":[{"value":"10 September 2020","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 September 2020","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}