{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T11:55:08Z","timestamp":1725796508263},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319093321"},{"type":"electronic","value":"9783319093338"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-09333-8_81","type":"book-chapter","created":{"date-parts":[[2014,7,3]],"date-time":"2014-07-03T06:22:38Z","timestamp":1404368558000},"page":"741-752","source":"Crossref","is-referenced-by-count":0,"title":["Online Model-Based Twin Parametric-Margin Support Vector Machine"],"prefix":"10.1007","author":[{"given":"Xinjun","family":"Peng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingyan","family":"Kong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongjing","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"81_CR1","first-page":"144","volume-title":"Proc. 5th Ann. Work. Comp. Lear. Theo.","author":"B. Boser","year":"1992","unstructured":"Boser, B., Guyon, L., Vapnik, V.N.: A training algorithm for optimal margin classifiers. In: Proc. 5th Ann. Work. Comp. Lear. Theo., pp. 144\u2013152. ACM Press, Pittsburgh (1992)"},{"key":"81_CR2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The natural of statistical learning theory","author":"V.N. Vapnik","year":"1995","unstructured":"Vapnik, V.N.: The natural of statistical learning theory. Springer, New York (1995)"},{"key":"81_CR3","volume-title":"Statistical learning theory","author":"V.N. Vapnik","year":"1998","unstructured":"Vapnik, V.N.: Statistical learning theory. Wiley, New York (1998)"},{"key":"81_CR4","unstructured":"Osuna, E., Freund, R., Girosi, F.: Training support vector machines: an application to face detection. In: Proc. IEEE Comp. Visi. Patt. Reco., San Juan, Puerto Rico, pp. 130\u2013136 (1997)"},{"key":"81_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/BFb0026683","volume-title":"Machine Learning: ECML-98","author":"T. Joachims","year":"1998","unstructured":"Joachims, T., Ndellec, C., Rouveriol, C.: Text categorization with support vector machines: Learning with many relevant features. In: N\u00e9dellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol.\u00a01398, pp. 137\u2013142. Springer, Heidelberg (1998)"},{"key":"81_CR6","unstructured":"Osuna, E., Freund, R., Girosi, F.: An improved training algorithm for support vector machines. In: Proc. IEEE Work. Neur. Netw. Sign. Proc., Amelia Island, FL, USA, pp. 276\u2013285 (1997)"},{"key":"81_CR7","first-page":"185","volume-title":"Adv. Kern. Meth.-Support Vector Learning","author":"J. Platt","year":"1999","unstructured":"Platt, J.: Fast training of support vector machines using sequential minimal optimization. In: Adv. Kern. Meth.-Support Vector Learning, pp. 185\u2013208. MIT Press, Cambridge (1999)"},{"key":"81_CR8","first-page":"169","volume-title":"Adv. Kern. Meth.-Support Vector Machine","author":"T. Joachims","year":"1999","unstructured":"Joachims, T.: Making large-scale SVM learning practical. In: Adv. Kern. Meth.-Support Vector Machine, pp. 169\u2013184. MIT Press, Cambridge (1999)"},{"key":"81_CR9","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1109\/TPAMI.2007.1068","volume":"29","author":"R. Jayadeva","year":"2007","unstructured":"Jayadeva, R., Khemchandani, S., Chandra: Twin support vector machines for pattern classification. IEEE Trans. Patte. Anal. Mach. Intel.\u00a029, 905\u2013910 (2007)","journal-title":"IEEE Trans. Patte. Anal. Mach. Intel."},{"key":"81_CR10","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.neunet.2009.07.002","volume":"23","author":"X. Peng","year":"2010","unstructured":"Peng, X.: TSVR: an efficient twin support vector machine for regression. Neur. Netw.\u00a023, 365\u2013372 (2010)","journal-title":"Neur. Netw."},{"key":"81_CR11","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.neucom.2011.09.021","volume":"79","author":"X. Peng","year":"2012","unstructured":"Peng, X.: Efficient twin parametric insensitive support vector regression model. Neurocomputing\u00a079, 26\u201338 (2012)","journal-title":"Neurocomputing"},{"key":"81_CR12","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.ins.2012.09.009","volume":"221","author":"X. Peng","year":"2013","unstructured":"Peng, X., Xu, D.: A twin-hypersphere support vector machine classifier and the fast learning algorithm. Infor. Scie.\u00a0221, 12\u201327 (2013)","journal-title":"Infor. Scie."},{"key":"81_CR13","doi-asserted-by":"publisher","first-page":"2678","DOI":"10.1016\/j.patcog.2011.03.031","volume":"44","author":"X. Peng","year":"2011","unstructured":"Peng, X.: TPMSVM: A novel twin parametric-margin support vector machine for pattern recognition. Patt. Reco.\u00a044, 2678\u20132692 (2011)","journal-title":"Patt. Reco."},{"key":"81_CR14","volume-title":"Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond","author":"B. Scholkopf","year":"2002","unstructured":"Scholkopf, B., Smola, A.: Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. MIT Press, Cambridge (2002)"},{"key":"81_CR15","doi-asserted-by":"publisher","first-page":"2165","DOI":"10.1109\/TSP.2004.830991","volume":"100","author":"J. Kivinen","year":"2004","unstructured":"Kivinen, J., Smola, A., Williamson, R.: Online learning with Kernels. IEEE Trans. Signal Proc.\u00a0100, 2165\u20132176 (2004)","journal-title":"IEEE Trans. Signal Proc."},{"key":"81_CR16","unstructured":"Ratsch, G.: Benchmark repository (2000), datasets available at \n                    \n                      http:\/\/ida.first.fhg.de\/projects\/bench\/benchmarks.htm"},{"issue":"3","key":"81_CR17","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1109\/TNNLS.2012.2229293","volume":"24","author":"G. Li","year":"2013","unstructured":"Li, G., Wen, C., Li, Z.: Model-based online learning with kernels. IEEE Trans. Neur. Netw. Lear. Syst.\u00a024(3), 356\u2013369 (2013)","journal-title":"IEEE Trans. Neur. Netw. Lear. Syst."}],"container-title":["Lecture Notes in Computer Science","Intelligent Computing Theory"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-09333-8_81","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,27]],"date-time":"2019-05-27T02:55:10Z","timestamp":1558925710000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-09333-8_81"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319093321","9783319093338"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-09333-8_81","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2014]]}}}