{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T07:33:56Z","timestamp":1767857636543,"version":"3.49.0"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2015,10,12]],"date-time":"2015-10-12T00:00:00Z","timestamp":1444608000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann Oper Res"],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1007\/s10479-015-2039-6","type":"journal-article","created":{"date-parts":[[2015,10,13]],"date-time":"2015-10-13T17:16:02Z","timestamp":1444756562000},"page":"45-68","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Robust chance-constrained support vector machines with second-order moment information"],"prefix":"10.1007","volume":"263","author":[{"given":"Ximing","family":"Wang","sequence":"first","affiliation":[]},{"given":"Neng","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Panos M.","family":"Pardalos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,10,12]]},"reference":[{"key":"2039_CR1","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-84996-098-4","volume-title":"Support vector machines for pattern classification","author":"S Abe","year":"2010","unstructured":"Abe, S. (2010). Support vector machines for pattern classification. Berlin: Springer."},{"key":"2039_CR2","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1007\/978-1-60327-241-4_13","volume-title":"Data mining techniques for the life sciences","author":"A Ben-Hur","year":"2010","unstructured":"Ben-Hur, A., & Weston, J. (2010). A users guide to support vector machines. In O. Carugo & F. Eisenhaber (Eds.), Data mining techniques for the life sciences (pp. 223\u2013239). Berlin: Springer."},{"issue":"1","key":"2039_CR3","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1007\/s10107-010-0415-1","volume":"127","author":"A Ben-Tal","year":"2011","unstructured":"Ben-Tal, A., Bhadra, S., Bhattacharyya, C., & Nath, J. S. (2011). Chance constrained uncertain classification via robust optimization. Mathematical Programming, 127(1), 145\u2013173.","journal-title":"Mathematical Programming"},{"issue":"3","key":"2039_CR4","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1137\/S1052623401399903","volume":"15","author":"D Bertsimas","year":"2005","unstructured":"Bertsimas, D., & Popescu, I. (2005). Optimal inequalities in probability theory: A convex optimization approach. Siam Journal on Optimization, 15(3), 780\u2013804.","journal-title":"Siam Journal on Optimization"},{"issue":"6","key":"2039_CR5","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1089\/cmb.2004.11.1073","volume":"11","author":"C Bhattacharyya","year":"2004","unstructured":"Bhattacharyya, C., Grate, L. R., Jordan, M. I., El Ghaoui, L., & Mian, I. S. (2004). Robust sparse hyperplane classifiers: Application to uncertain molecular profiling data. Journal of Computational Biology, 11(6), 1073\u20131089.","journal-title":"Journal of Computational Biology"},{"key":"2039_CR6","volume-title":"Advances in neural information processing systems 17: Proceedings of the 2004 conference","author":"J Bi","year":"2005","unstructured":"Bi, J., & Zhang, T. (2005). Support vector classification with input data uncertainty. In L. K. Saul, Y. Weiss, & L. Bottou (Eds.), Advances in neural information processing systems 17: Proceedings of the 2004 conference. Cambridge: MIT Press."},{"issue":"2","key":"2039_CR7","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"CJ Burges","year":"1998","unstructured":"Burges, C. J. (1998). A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2), 121\u2013167.","journal-title":"Data Mining and Knowledge Discovery"},{"issue":"3","key":"2039_CR8","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang, C. C., & Lin, C. J. (2011). Libsvm: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3), 27.","journal-title":"ACM Transactions on Intelligent Systems and Technology"},{"issue":"3","key":"2039_CR9","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273\u2013297.","journal-title":"Machine Learning"},{"key":"2039_CR10","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/978-3-319-09584-4_26","volume-title":"Learning and intelligent optimization","author":"N Fan","year":"2014","unstructured":"Fan, N., Sadeghi, E., & Pardalos, P. M. (2014). Robust support vector machines with polyhedral uncertainty of the input data. In P. M. Pardalos, M. G. C. Resende, C. Vogiatzis, & J. L. Walteros (Eds.), Learning and intelligent optimization (pp. 291\u2013305). Berlin: Springer."},{"key":"2039_CR11","unstructured":"Ghaoui, L. E., Lanckriet, G. R., & Natsoulis, G. (2003). Robust classification with interval data. Technical report UCB\/CSD-03-1279, Computer Science Division, University of California, Berkeley."},{"issue":"4","key":"2039_CR12","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1287\/opre.51.4.543.16101","volume":"51","author":"LE Ghaoui","year":"2003","unstructured":"Ghaoui, L. E., Oks, M., & Oustry, F. (2003). Worst-case value-at-risk and robust portfolio optimization: A conic programming approach. Operations Research, 51(4), 543\u2013556.","journal-title":"Operations Research"},{"issue":"2","key":"2039_CR13","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/BF01733120","volume":"12","author":"K Isii","year":"1960","unstructured":"Isii, K. (1960). The extrema of probability determined by generalized moments (i) bounded random variables. Annals of the Institute of Statistical Mathematics, 12(2), 119\u2013134.","journal-title":"Annals of the Institute of Statistical Mathematics"},{"key":"2039_CR14","first-page":"555","volume":"3","author":"GR Lanckriet","year":"2002","unstructured":"Lanckriet, G. R., Ghaoui, L. E., Bhattacharyya, C., & Jordan, M. I. (2002). A robust minimax approach to classification. Journal of Machine Learning Research, 3, 555\u2013582.","journal-title":"Journal of Machine Learning Research"},{"issue":"4","key":"2039_CR15","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1214\/aoms\/1177705673","volume":"31","author":"AW Marshall","year":"1960","unstructured":"Marshall, A. W., & Olkin, I. (1960). Multivariate chebyshev inequalities. The Annals of Mathematical Statistics, 31(4), 1001\u20131014.","journal-title":"The Annals of Mathematical Statistics"},{"key":"2039_CR16","unstructured":"Pant, R., Trafalis, T. B., & Barker, K. (2011). Support vector machine classification of uncertain and imbalanced data using robust optimization. In Proceedings of the 15th WSEAS international conference on computers (pp. 369\u2013374). World Scientific and Engineering Academy and Society (WSEAS)."},{"issue":"3","key":"2039_CR17","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1137\/S003614450444614X","volume":"49","author":"I P\u00f3lik","year":"2007","unstructured":"P\u00f3lik, I., & Terlaky, T. (2007). A survey of the s-lemma. SIAM Review, 49(3), 371\u2013418.","journal-title":"SIAM Review"},{"key":"2039_CR18","first-page":"1283","volume":"7","author":"PK Shivaswamy","year":"2006","unstructured":"Shivaswamy, P. K., Bhattacharyya, C., & Smola, A. J. (2006). Second order cone programming approaches for handling missing and uncertain data. Journal of Machine Learning Research, 7, 1283\u20131314.","journal-title":"Journal of Machine Learning Research"},{"issue":"1","key":"2039_CR19","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3846\/20294913.2012.661205","volume":"18","author":"Y Tian","year":"2012","unstructured":"Tian, Y., Shi, Y., & Liu, X. (2012). Recent advances on support vector machines research. Technological and Economic Development of Economy, 18(1), 5\u201333.","journal-title":"Technological and Economic Development of Economy"},{"issue":"7","key":"2039_CR20","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1080\/03081079.2010.504340","volume":"39","author":"TB Trafalis","year":"2010","unstructured":"Trafalis, T. B., & Alwazzi, S. A. (2010). Support vector machine classification with noisy data: A second order cone programming approach. International Journal of General Systems, 39(7), 757\u2013781.","journal-title":"International Journal of General Systems"},{"issue":"3","key":"2039_CR21","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1016\/j.ejor.2005.07.024","volume":"173","author":"TB Trafalis","year":"2006","unstructured":"Trafalis, T. B., & Gilbert, R. C. (2006). Robust classification and regression using support vector machines. European Journal of Operational Research, 173(3), 893\u2013909.","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"2039_CR22","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1080\/10556780600883791","volume":"22","author":"TB Trafalis","year":"2007","unstructured":"Trafalis, T. B., & Gilbert, R. C. (2007). Robust support vector machines for classification and computational issues. Optimization Methods and Software, 22(1), 187\u2013198.","journal-title":"Optimization Methods and Software"},{"key":"2039_CR23","volume-title":"Statistical learning theory","author":"VN Vapnik","year":"1998","unstructured":"Vapnik, V. N. (1998). Statistical learning theory. New York: Wiley."},{"issue":"5","key":"2039_CR24","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1109\/72.788640","volume":"10","author":"VN Vapnik","year":"1999","unstructured":"Vapnik, V. N. (1999). An overview of statistical learning theory. IEEE Transactions on Neural Networks, 10(5), 988\u2013999.","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"3\u20134","key":"2039_CR25","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1007\/s40745-014-0022-8","volume":"1","author":"X Wang","year":"2014","unstructured":"Wang, X., & Pardalos, P. M. (2014). A survey of support vector machines with uncertainties. Annals of Data Science, 1(3\u20134), 293\u2013309.","journal-title":"Annals of Data Science"},{"issue":"1","key":"2039_CR26","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1007\/s10479-012-1303-2","volume":"216","author":"P Xanthopoulos","year":"2014","unstructured":"Xanthopoulos, P., Guarracino, M. R., & Pardalos, P. M. (2014). Robust generalized eigenvalue classifier with ellipsoidal uncertainty. Annals of Operations Research, 216(1), 327\u2013342.","journal-title":"Annals of Operations Research"},{"key":"2039_CR27","volume-title":"Robust data mining","author":"P Xanthopoulos","year":"2012","unstructured":"Xanthopoulos, P., Pardalos, P. M., & Trafalis, T. B. (2012). Robust data mining. Berlin: Springer."},{"key":"2039_CR28","first-page":"62","volume":"1","author":"VA Yakubovich","year":"1971","unstructured":"Yakubovich, V. A. (1971). S-procedure in nonlinear control theory. Vestnik Leningrad University, 1, 62\u201377.","journal-title":"Vestnik Leningrad University"},{"issue":"1\u20132","key":"2039_CR29","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s10107-011-0494-7","volume":"137","author":"S Zymler","year":"2013","unstructured":"Zymler, S., Kuhn, D., & Rustem, B. (2013). Distributionally robust joint chance constraints with second-order moment information. Mathematical Programming, 137(1\u20132), 167\u2013198.","journal-title":"Mathematical Programming"}],"container-title":["Annals of Operations Research"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-015-2039-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10479-015-2039-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-015-2039-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-015-2039-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,31]],"date-time":"2019-08-31T10:05:45Z","timestamp":1567245945000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10479-015-2039-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,10,12]]},"references-count":29,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["2039"],"URL":"https:\/\/doi.org\/10.1007\/s10479-015-2039-6","relation":{},"ISSN":["0254-5330","1572-9338"],"issn-type":[{"value":"0254-5330","type":"print"},{"value":"1572-9338","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,10,12]]}}}