{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:04:44Z","timestamp":1740096284529,"version":"3.37.3"},"publisher-location":"Berlin, Heidelberg","reference-count":12,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642400193"},{"type":"electronic","value":"9783642400209"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-40020-9_75","type":"book-chapter","created":{"date-parts":[[2013,8,18]],"date-time":"2013-08-18T21:32:37Z","timestamp":1376861557000},"page":"677-684","source":"Crossref","is-referenced-by-count":1,"title":["Learning General Gaussian Kernel Hyperparameters for SVR"],"prefix":"10.1007","author":[{"given":"F.","family":"Abdallah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hichem","family":"Snoussi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H.","family":"Laanaya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Lengell\u00e9","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"75_CR1","unstructured":"Vapnik, V.N.: Statistical Learning Theory. John Wesley and Sons (1998)"},{"issue":"1-2","key":"75_CR2","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/S0925-2312(03)00375-8","volume":"55","author":"C. Gold","year":"2003","unstructured":"Gold, C., Sollich, P.: Model selection for support vector machine classification. Neurocomputing\u00a055(1-2), 221\u2013249 (2003), \n                    \n                      http:\/\/dx.doi.org\/10.1016\/S0925-23120300375-8","journal-title":"Neurocomputing"},{"key":"75_CR3","unstructured":"Grandvalet, Y., Canu, S.: Adaptive scaling for feature selection in SVMs. In: Becker, S., Thrun, S., Obermayer, K. (eds.) NIPS, pp. 553\u2013560. MIT Press (2002), \n                    \n                      http:\/\/books.nips.cc\/papers\/files\/nips15\/AA09.pdf"},{"key":"75_CR4","first-page":"27","volume":"5","author":"G.R.G. Lanckriet","year":"2004","unstructured":"Lanckriet, G.R.G., Cristianini, N., Bartlett, P., Ghaoui, L.E., Jordan, M.I.: Learning the kernel matrix with semidefinite programming. Journal of Machine Learning Research\u00a05, 27\u201372 (2004)","journal-title":"Journal of Machine Learning Research"},{"issue":"3-4","key":"75_CR5","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/S0925-2312(02)00632-X","volume":"55","author":"W. Wang","year":"2003","unstructured":"Wang, W., Xu, Z., Lu, W., Zhang, X.: Determination of the spread parameter in the gaussian kernel for classification and regression. Neurocomputing\u00a055(3-4), 643\u2013663 (2003), \n                    \n                      http:\/\/dx.doi.org\/10.1016\/S0925-23120200632-X","journal-title":"Neurocomputing"},{"issue":"1-3","key":"75_CR6","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1016\/j.neucom.2007.11.010","volume":"72","author":"W. He","year":"2008","unstructured":"He, W., Wang, Z., Jiang, H.: Model optimizing and feature selecting for support vector regression in time series forecasting. Neurocomputing\u00a072(1-3), 600\u2013611 (2008), \n                    \n                      http:\/\/dx.doi.org\/10.1016\/j.neucom.2007.11.010","journal-title":"Neurocomputing"},{"key":"75_CR7","unstructured":"Qiu, S., Lane, T.: Multiple kernel learning for support vector regression. University of New Mexico, Tech. Rep. (2005)"},{"key":"75_CR8","doi-asserted-by":"crossref","DOI":"10.1515\/9781400830244","volume-title":"Optimization Algorithms on Matrix Manifolds","author":"P.-A. Absil","year":"2008","unstructured":"Absil, P.-A., Mahony, R., Sepulchre, R.: Optimization Algorithms on Matrix Manifolds. Princeton University Press, Princeton (2008)"},{"key":"75_CR9","unstructured":"Amari, S., Nagaoka, H.: Methods of Information Geometry. American Mathematical Society (2000)"},{"key":"75_CR10","unstructured":"Asuncion, D.N.A.: UCI machine learning repository (2007), \n                    \n                      http:\/\/www.ics.uci.edu\/~mlearn\/MLRepository.html"},{"issue":"1\/3","key":"75_CR11","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1023\/A:1012474916001","volume":"46","author":"G.W. Flake","year":"2002","unstructured":"Flake, G.W., Lawrence, S.: Efficient SVM regression training with SMO. Machine Learning\u00a046(1\/3), 271 (2002)","journal-title":"Machine Learning"},{"issue":"3","key":"75_CR12","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1016\/S0167-7152(96)00140-X","volume":"33","author":"R. Kelley Pace","year":"1997","unstructured":"Kelley Pace, R., Barry, R.: Sparse spatial autoregressions. Statistics & Probability Letters\u00a033(3), 291\u2013297 (1997), \n                    \n                      http:\/\/ideas.repec.org\/a\/eee\/stapro\/v33y1997i3p291-297.html","journal-title":"Statistics & Probability Letters"}],"container-title":["Lecture Notes in Computer Science","Geometric Science of Information"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-40020-9_75","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,16]],"date-time":"2019-05-16T14:20:54Z","timestamp":1558016454000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-40020-9_75"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642400193","9783642400209"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-40020-9_75","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2013]]}}}