{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T12:40:07Z","timestamp":1746362407738,"version":"3.40.4"},"publisher-location":"Berlin, Heidelberg","reference-count":23,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783662448472"},{"type":"electronic","value":"9783662448489"}],"license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-662-44848-9_37","type":"book-chapter","created":{"date-parts":[[2014,9,1]],"date-time":"2014-09-01T05:42:21Z","timestamp":1409550141000},"page":"579-594","source":"Crossref","is-referenced-by-count":4,"title":["Transductive Minimax Probability Machine"],"prefix":"10.1007","author":[{"given":"Gao","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiji","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhixiang (Eddie)","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kilian","family":"Weinberger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"37_CR1","first-page":"2399","volume":"7","author":"M. Belkin","year":"2006","unstructured":"Belkin, M., Niyogi, P., Sindhwani, V.: Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. The Journal of Machine Learning Research\u00a07, 2399\u20132434 (2006)","journal-title":"The Journal of Machine Learning Research"},{"key":"37_CR2","doi-asserted-by":"crossref","unstructured":"Bertsimas, D., Sethuraman, J.: Moment problems and semidefinite optimization. In: Handbook of Semidefinite Programming, pp. 469\u2013509. Springer (2000)","DOI":"10.1007\/978-1-4615-4381-7_16"},{"key":"37_CR3","unstructured":"Bhattacharyya, C., Pannagadatta, K., Smola, A.J.: A second order cone programming formulation for classifying missing data. In: Neural Information Processing Systems (NIPS), pp. 153\u2013160 (2005)"},{"key":"37_CR4","volume-title":"Pattern recognition and machine learning","author":"C.M. Bishop","year":"2006","unstructured":"Bishop, C.M., Nasrabadi, N.M.: Pattern recognition and machine learning, vol.\u00a01. Springer, New York (2006)"},{"key":"37_CR5","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262033589.001.0001","volume-title":"Semi-supervised learning","author":"O. Chapelle","year":"2006","unstructured":"Chapelle, O., Sch\u00f6lkopf, B., Zien, A., et al.: Semi-supervised learning, vol.\u00a02. MIT Press, Cambridge (2006)"},{"key":"37_CR6","unstructured":"Chapelle, O., Zien, A.: Semi-supervised classification by low density separation. In: Proceedings of the 10th International Conference on Artificial Intelligence and Statistics, pp. 57\u201364 (2005)"},{"issue":"12","key":"37_CR7","doi-asserted-by":"publisher","first-page":"3548","DOI":"10.1016\/j.patcog.2013.06.016","volume":"46","author":"G. Huang","year":"2013","unstructured":"Huang, G., Song, S., Gupta, J.N.D., Wu, C.: A second order cone programming approach for semi-supervised learning. Pattern Recognition\u00a046(12), 3548\u20133558 (2013)","journal-title":"Pattern Recognition"},{"issue":"1","key":"37_CR8","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/BF02868641","volume":"14","author":"K. Isii","year":"1962","unstructured":"Isii, K.: On sharpness of tchebycheff-type inequalities. Annals of the Institute of Statistical Mathematics\u00a014(1), 185\u2013197 (1962)","journal-title":"Annals of the Institute of Statistical Mathematics"},{"key":"37_CR9","unstructured":"Joachims, T.: Transductive inference for text classification using support vector machines. In: ICML, vol.\u00a099, pp. 200\u2013209 (1999)"},{"key":"37_CR10","unstructured":"Joachims, T., et al.: Transductive learning via spectral graph partitioning. In: ICML, vol.\u00a03, pp. 290\u2013297 (2003)"},{"key":"37_CR11","doi-asserted-by":"crossref","unstructured":"Korte, B.B.H., Vygen, J.: Combinatorial optimization, vol.\u00a021. Springer (2012)","DOI":"10.1007\/978-3-642-24488-9"},{"key":"37_CR12","unstructured":"Krummenacher, G., Ong, C.S., Buhmann, J.: Ellipsoidal multiple instance learning. In: Proceedings of the 30th International Conference on Machine Learning, pp. 73\u201381 (2013)"},{"key":"37_CR13","first-page":"555","volume":"3","author":"G.R. Lanckriet","year":"2003","unstructured":"Lanckriet, G.R., Ghaoui, L.E., Bhattacharyya, C., Jordan, M.I.: A robust minimax approach to classification. The Journal of Machine Learning Research\u00a03, 555\u2013582 (2003)","journal-title":"The Journal of Machine Learning Research"},{"issue":"2-3","key":"37_CR14","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1023\/A:1007692713085","volume":"39","author":"K. Nigam","year":"2000","unstructured":"Nigam, K., McCallum, A.K., Thrun, S., Mitchell, T.: Text classification from labeled and unlabeled documents using em. Machine Learning\u00a039(2-3), 103\u2013134 (2000)","journal-title":"Machine Learning"},{"key":"37_CR15","unstructured":"Niu, G., Jitkrittum, W., Dai, B., Hachiya, H., Sugiyama, M.: Squared-loss mutual information regularization: A novel information-theoretic approach to semi-supervised learning. In: Proceedings of the 30th International Conference on Machine Learning, pp. 10\u201318 (2013)"},{"key":"37_CR16","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., Smola, A.J.: Learning with kernels. MIT Press (2002)","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"37_CR17","first-page":"1283","volume":"7","author":"P.K. Shivaswamy","year":"2006","unstructured":"Shivaswamy, P.K., Bhattacharyya, C., Smola, A.J.: Second order cone programming approaches for handling missing and uncertain data. The Journal of Machine Learning Research\u00a07, 1283\u20131314 (2006)","journal-title":"The Journal of Machine Learning Research"},{"key":"37_CR18","doi-asserted-by":"crossref","unstructured":"Sindhwani, V., Keerthi, S.S.: Large scale semi-supervised linear svms. In: Proceedings of the 29th annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 477\u2013484. ACM (2006)","DOI":"10.1145\/1148170.1148253"},{"key":"37_CR19","doi-asserted-by":"crossref","unstructured":"Sindhwani, V., Niyogi, P., Belkin, M.: Beyond the point cloud: from transductive to semi-supervised learning. In: ICML 2005, pp. 824\u2013831. ACM (2005)","DOI":"10.1145\/1102351.1102455"},{"key":"37_CR20","unstructured":"Vapnik, V.N.: Statistical learning theory (1998)"},{"key":"37_CR21","doi-asserted-by":"crossref","unstructured":"Weinberger, K.Q., Sha, F., Zhu, Q., Saul, L.K.: Graph laplacian regularization for large-scale semidefinite programming. In: NIPS, pp. 1489\u20131496 (2006)","DOI":"10.7551\/mitpress\/7503.003.0191"},{"key":"37_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1007\/978-3-642-28258-4_5","volume-title":"Partially Supervised Learning","author":"K. Yoshiyama","year":"2012","unstructured":"Yoshiyama, K., Sakurai, A.: Manifold-regularized minimax probability machine. In: Schwenker, F., Trentin, E. (eds.) PSL 2011. LNCS, vol.\u00a07081, pp. 42\u201351. Springer, Heidelberg (2012)"},{"key":"37_CR23","first-page":"3","volume":"2","author":"X. Zhu","year":"2006","unstructured":"Zhu, X.: Semi-supervised learning literature survey. Computer Science, University of Wisconsin-Madison\u00a02, 3 (2006)","journal-title":"Computer Science, University of Wisconsin-Madison"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-662-44848-9_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T12:16:06Z","timestamp":1746360966000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-662-44848-9_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783662448472","9783662448489"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-662-44848-9_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2014]]}}}