{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T05:08:16Z","timestamp":1791522496566,"version":"4.3.4"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2014,9,4]],"date-time":"2014-09-04T00:00:00Z","timestamp":1409788800000},"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":["Stat Comput"],"published-print":{"date-parts":[[2015,11]]},"DOI":"10.1007\/s11222-014-9505-x","type":"journal-article","created":{"date-parts":[[2014,9,3]],"date-time":"2014-09-03T04:57:26Z","timestamp":1409720246000},"page":"1143-1162","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Kernel discriminant analysis and clustering with parsimonious Gaussian process models"],"prefix":"10.1007","volume":"25","author":[{"given":"C.","family":"Bouveyron","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Fauvel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Girard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2014,9,4]]},"reference":[{"issue":"6","key":"9505_CR1","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","volume":"19","author":"Hirotugu Akaike","year":"1974","unstructured":"Akaike, Hirotugu: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716\u2013723 (1974)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"5","key":"9505_CR2","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.1007\/s11222-011-9272-x","volume":"22","author":"JL Andrews","year":"2012","unstructured":"Andrews, J.L., McNicholas, P.D.: Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions. Stat. Comput. 22(5), 1021\u20131029 (2012)","journal-title":"Stat. Comput."},{"issue":"7","key":"9505_CR3","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1109\/34.865189","volume":"22","author":"C Biernacki","year":"2001","unstructured":"Biernacki, C., Celeux, G., Govaert, G.: Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Trans. Pattern Anal. Mach. Intell. 22(7), 719\u2013725 (2001)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9505_CR4","doi-asserted-by":"crossref","unstructured":"Bouguila, N., Ziou, D., Vaillancourt, J.: Novel mixtures based on the Dirichlet distribution: application to data and image classification. In: Machine Learning and Data Mining in Pattern Recognition, pp. 172\u2013181. Springer, Berlin (2003)","DOI":"10.1007\/3-540-45065-3_15"},{"issue":"1","key":"9505_CR5","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s11222-011-9249-9","volume":"22","author":"C Bouveyron","year":"2012","unstructured":"Bouveyron, C., Brunet, C.: Simultaneous model-based clustering and visualization in the Fisher discriminative subspace. Stat. Comput. 22(1), 301\u2013324 (2012)","journal-title":"Stat. Comput."},{"key":"9505_CR6","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.csda.2012.12.008","volume":"71","author":"C Bouveyron","year":"2013","unstructured":"Bouveyron, C., Brunet-Saumard, C.: Model-based clustering of high-dimensional data: a review. Comput. Stat. Data Anal. 71, 52\u201378 (2013)","journal-title":"Comput. Stat. Data Anal."},{"issue":"11","key":"9505_CR7","doi-asserted-by":"crossref","first-page":"2649","DOI":"10.1016\/j.patcog.2009.03.027","volume":"42","author":"C Bouveyron","year":"2009","unstructured":"Bouveyron, C., Girard, S.: Robust supervised classification with mixture models: learning from data with uncertain labels. Pattern Recognit. 42(11), 2649\u20132658 (2009)","journal-title":"Pattern Recognit."},{"issue":"4","key":"9505_CR8","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s11634-011-0095-6","volume":"5","author":"C Bouveyron","year":"2011","unstructured":"Bouveyron, C., Jacques, J.: Model-based clustering of time series in group-specific functional subspaces. Adv. Data Anal. Classif. 5(4), 281\u2013300 (2011)","journal-title":"Adv. Data Anal. Classif."},{"key":"9505_CR9","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1080\/03610920701271095","volume":"36","author":"C Bouveyron","year":"2007","unstructured":"Bouveyron, C., Girard, S., Schmid, C.: High-dimensional discriminant analysis. Commun. Stat. 36, 2607\u20132623 (2007a)","journal-title":"Commun. Stat."},{"key":"9505_CR10","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1016\/j.csda.2007.02.009","volume":"52","author":"C Bouveyron","year":"2007","unstructured":"Bouveyron, C., Girard, S., Schmid, C.: High-dimensional data clustering. Comput. Stat. Data Anal. 52, 502\u2013519 (2007b)","journal-title":"Comput. Stat. Data Anal."},{"key":"9505_CR11","unstructured":"Canu, S., Grandvalet, Y., Guigue, V., Rakotomamonjy, A.: SVM and kernel methods matlab toolbox. In: Perception Systemes et Information. INSA de Rouen, Rouen (2005)"},{"key":"9505_CR12","first-page":"16151646","volume":"68","author":"A Caponnetto","year":"2008","unstructured":"Caponnetto, A., Micchelli, C.A., Pontil, M., Ying, Y.: Universal multi-task kernels. J. Mach. Learn. Res. 68, 16151646 (2008)","journal-title":"J. Mach. Learn. Res."},{"issue":"2","key":"9505_CR13","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1207\/s15327906mbr0102_10","volume":"1","author":"R Cattell","year":"1966","unstructured":"Cattell, R.: The scree test for the number of factors. Multivar. Behav. Res. 1(2), 245\u2013276 (1966)","journal-title":"Multivar. Behav. Res."},{"issue":"2","key":"9505_CR14","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/BF02616237","volume":"8","author":"G Celeux","year":"1991","unstructured":"Celeux, G., Govaert, G.: Clustering criteria for discrete data and latent class models. J. Classif. 8(2), 157\u2013176 (1991)","journal-title":"J. Classif."},{"key":"9505_CR15","doi-asserted-by":"crossref","unstructured":"Chapelle, O., Sch\u00f6lkopf, B., Zien, A. (eds.): Semi-Supervised Learning. MIT Press, Cambridge. http:\/\/www.kyb.tuebingen.mpg.de\/ssl-book (2006)","DOI":"10.7551\/mitpress\/9780262033589.001.0001"},{"key":"9505_CR16","doi-asserted-by":"crossref","unstructured":"Couto, J.: Kernel k-means for categorical data. In: Advances in Intelligent Data Analysis VI, vol. 3646 of Lecture Notes in Computer Science, pp. 739\u2013739. Springer, Berlin (2005)","DOI":"10.1007\/11552253_5"},{"issue":"8","key":"9505_CR17","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1016\/j.neunet.2005.07.010","volume":"18","author":"M Cuturi","year":"2005","unstructured":"Cuturi, M., Vert, J.P.: The context-tree kernel for strings. Neural Netw. 18(8), 1111\u20131123 (2005)","journal-title":"Neural Netw."},{"issue":"1","key":"9505_CR18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"A Dempster","year":"1977","unstructured":"Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 39(1), 1\u201338 (1977)","journal-title":"J. R. Stat. Soc. Ser. B"},{"issue":"1","key":"9505_CR19","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1109\/TGRS.2003.817813","volume":"42","author":"MM Dundar","year":"2004","unstructured":"Dundar, M.M., Landgrebe, D.A.: Toward an optimal supervised classifier for the analysis of hyperspectral data. IEEE Trans. Geosci. Remote Sens. 42(1), 271\u2013277 (2004)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"9505_CR20","first-page":"615637","volume":"6","author":"T Evgeniou","year":"2005","unstructured":"Evgeniou, T., Micchelli, C.A., Pontil, M.: Learning multiple tasks with kernel methods. J. Mach. Learn. Res. 6, 615637 (2005)","journal-title":"J. Mach. Learn. Res."},{"key":"9505_CR21","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1111\/j.1469-1809.1936.tb02137.x","volume":"7","author":"RA Fisher","year":"1936","unstructured":"Fisher, R.A.: The use of multiple measurements in taxonomic problems. Ann. Eugenics 7, 179\u2013188 (1936)","journal-title":"Ann. Eugenics"},{"key":"9505_CR22","doi-asserted-by":"crossref","unstructured":"Forbes, F., Wraith, D.: A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: application to robust clustering. Stat. Comput. (to appear) (2014)","DOI":"10.1007\/s11222-013-9414-4"},{"issue":"6","key":"9505_CR23","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1109\/TPAMI.2013.216","volume":"36","author":"BC Franczak","year":"2014","unstructured":"Franczak, B.C., Browne, R.P., McNicholas, P.D.: Mixtures of shifted asymmetric Laplace distributions. IEEE Trans. Pattern Anal. Mach. Intell. 36(6), 1149\u20131157 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"9505_CR24","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1109\/TNN.2002.1000150","volume":"13","author":"M Girolami","year":"2002","unstructured":"Girolami, M.: Mercer kernel-based clustering in feature space. IEEE Trans. Neural Netw. 13(3), 780\u2013784 (2002)","journal-title":"IEEE Trans. Neural Netw."},{"key":"9505_CR25","first-page":"2211","volume":"12","author":"M G\u00f6nen","year":"2011","unstructured":"G\u00f6nen, M., Alpaydin, E.: Multiple kernel learning algorithms. J. Mach. Learn. Res. 12, 2211\u20132268 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"9505_CR26","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1214\/009053607000000677","volume":"36","author":"T Hofmann","year":"2008","unstructured":"Hofmann, T., Sch\u00f6lkopf, B., Smola, A.: Kernel methods in machine learning. Ann. Stat. 36(3), 1171\u20131220 (2008)","journal-title":"Ann. Stat."},{"key":"9505_CR27","unstructured":"Kadri, H., Rakotomamonjy, A., Bach, F., Preux, P.: Multiple Operator-Valued Kernel Learning. In: Neural Information Processing Systems (NIPS), pp. 1172\u20131080 (2012)"},{"key":"9505_CR28","first-page":"1679","volume":"6","author":"M Kuss","year":"2005","unstructured":"Kuss, M., Rasmussen, C.: Assessing approximate inference for binary Gaussian process classification. J. Mach. Learn. Res. 6, 1679\u20131704 (2005)","journal-title":"J. Mach. Learn. Res."},{"issue":"2","key":"9505_CR29","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s11222-012-9362-4","volume":"24","author":"S Lee","year":"2013","unstructured":"Lee, S., McLachlan, G.J.: Finite mixtures of multivariate skew t-distributions: some recent and new results. Stat. Comput. 24(2), 181\u2013202 (2013)","journal-title":"Stat. Comput."},{"issue":"4","key":"9505_CR30","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1137\/S0895479895281484","volume":"17","author":"R Lehoucq","year":"1996","unstructured":"Lehoucq, R., Sorensen, D.: Deflation techniques for an implicitly restarted arnoldi iteration. SIAM J. Matrix Anal. Appl. 17(4), 789\u2013821 (1996)","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"9505_CR31","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/s11222-009-9128-9","volume":"20","author":"TI Lin","year":"2010","unstructured":"Lin, T.I.: Robust mixture modeling using multivariate skew t distribution. Stat. Comput. 20, 343\u2013356 (2010)","journal-title":"Stat. Comput."},{"key":"9505_CR32","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/s11222-006-9005-8","volume":"17","author":"TI Lin","year":"2007","unstructured":"Lin, T.I., Lee, J.C., Hsieh, W.J.: Robust mixture modeling using the skew t distribution. Stat. Comput. 17, 81\u201392 (2007)","journal-title":"Stat. Comput."},{"issue":"1","key":"9505_CR33","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10994-008-5086-2","volume":"75","author":"P Mah\u00e9","year":"2009","unstructured":"Mah\u00e9, P., Vert, J.P.: Graph kernels based on tree patterns for molecules. Mach. Learn. 75(1), 3\u201335 (2009)","journal-title":"Mach. Learn."},{"key":"9505_CR34","doi-asserted-by":"crossref","DOI":"10.1002\/0471725293","volume-title":"Discriminant Analysis and Statistical Pattern Recognition","author":"G McLachlan","year":"1992","unstructured":"McLachlan, G.: Discriminant Analysis and Statistical Pattern Recognition. Wiley, New York (1992)"},{"key":"9505_CR35","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/S0167-9473(02)00183-4","volume":"41","author":"G McLachlan","year":"2003","unstructured":"McLachlan, G., Peel, D., Bean, R.: Modelling high-dimensional data by mixtures of factor analyzers. Comput. Stat. Data Anal. 41, 379\u2013388 (2003)","journal-title":"Comput. Stat. Data Anal."},{"issue":"3","key":"9505_CR36","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/s11222-008-9056-0","volume":"18","author":"P McNicholas","year":"2008","unstructured":"McNicholas, P., Murphy, B.: Parsimonious Gaussian mixture models. Stat. Comput. 18(3), 285\u2013296 (2008)","journal-title":"Stat. Comput."},{"key":"9505_CR37","doi-asserted-by":"crossref","unstructured":"Mika, S., Ratsch, G., Weston, J., Sch\u00f6lkopf, B., M\u00fcllers, K.R.: Fisher discriminant analysis with kernels. In: Neural Networks for Signal Processing (NIPS), pp. 41\u201348 (1999)","DOI":"10.1109\/NNSP.1999.788121"},{"key":"9505_CR38","unstructured":"Minka, T.: Expectation propagation for approximate bayesian inference. In: Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, pp. 362\u2013369. Morgan Kaufmann, San Francisco (2001)"},{"issue":"4","key":"9505_CR39","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1177\/1471082X0901000405","volume":"10","author":"A Montanari","year":"2010","unstructured":"Montanari, A., Viroli, C.: Heteroscedastic factor mixture analysis. Stat. Model. 10(4), 441\u2013460 (2010)","journal-title":"Stat. Model."},{"issue":"1","key":"9505_CR40","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1214\/09-AOAS279","volume":"4","author":"TB Murphy","year":"2010","unstructured":"Murphy, T.B., Dean, N., Raftery, A.E.: Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications. Ann. Appl. Stat. 4(1), 219\u2013223 (2010)","journal-title":"Ann. Appl. Stat."},{"key":"9505_CR41","doi-asserted-by":"crossref","unstructured":"Murua, A., Wicker, N.: Kernel-based Mixture Models for Classification. Technical Report, University of Montr\u00e9al (2014)","DOI":"10.1007\/s00180-014-0535-9"},{"issue":"6","key":"9505_CR42","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1109\/TPAMI.2008.290","volume":"31","author":"E Pekalska","year":"2009","unstructured":"Pekalska, E., Haasdonk, B.: Kernel discriminant analysis for positive definite and indefinite kernels. IEEE Trans. Pattern Anal. Mach. Intell. 31(6), 1017\u20131032 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9505_CR43","doi-asserted-by":"crossref","DOI":"10.1007\/b98888","volume-title":"Functional Data Analysis. Springer Series in Statistics","author":"JO Ramsay","year":"2005","unstructured":"Ramsay, J.O., Silverman, B.W.: Functional Data Analysis. Springer Series in Statistics, 2nd edn. Springer, New York (2005)","edition":"2"},{"key":"9505_CR44","volume-title":"Gaussian Processes for Machine Learning Matlab Toolbox","author":"C Rasmussen","year":"2006","unstructured":"Rasmussen, C., Williams, C.: Gaussian Processes for Machine Learning Matlab Toolbox. MIT, Cambridge (2006a)"},{"key":"9505_CR45","volume-title":"Gaussian Processes for Machine Learning","author":"C Rasmussen","year":"2006","unstructured":"Rasmussen, C., Williams, C.: Gaussian Processes for Machine Learning. MIT, Cambridge (2006b)"},{"key":"9505_CR46","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/4175.001.0001","volume-title":"Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond","author":"B Scholkopf","year":"2001","unstructured":"Scholkopf, B., Smola, A.: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT, Cambridge (2001)"},{"issue":"5","key":"9505_CR47","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1162\/089976698300017467","volume":"10","author":"B Sch\u00f6lkopf","year":"1998","unstructured":"Sch\u00f6lkopf, B., Smola, A., M\u00fcller, K.-R.: Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput. 10(5), 1299\u20131319 (1998)","journal-title":"Neural Comput."},{"key":"9505_CR48","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., Tsuda, K., Vert, J.-P. (eds.): Kernel Methods in Computational Biology. MIT, Cambridge (2004)","DOI":"10.7551\/mitpress\/4057.001.0001"},{"key":"9505_CR49","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz, G.: Estimating the dimension of a model. Ann. Stat. 6, 461\u2013464 (1978)","journal-title":"Ann. Stat."},{"key":"9505_CR50","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511809682","volume-title":"Kernel Methods for Pattern Analysis","author":"J Shawe-Taylor","year":"2004","unstructured":"Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. Cambridge University Press, Cambridge (2004)"},{"key":"9505_CR51","volume-title":"Empirical Processes with Applications to Statistics","author":"GR Shorack","year":"1986","unstructured":"Shorack, G.R., Wellner, J.A.: Empirical Processes with Applications to Statistics. Wiley, New York (1986)"},{"key":"9505_CR52","doi-asserted-by":"crossref","unstructured":"Smola, A., Kondor, R.: Kernels and regularization on graphs. In: Proceedings of Conference on Learning Theory and Kernel Machines, pp. 144\u2013158 (2003)","DOI":"10.1007\/978-3-540-45167-9_12"},{"key":"9505_CR53","doi-asserted-by":"crossref","unstructured":"Wang, J., Lee, J., Zhang, C.: Kernel trick embedded Gaussian mixture model. In: Proceedings of the 14th International Conference on Algorithmic Learning Theory, pp. 159\u2013174 (2003)","DOI":"10.1007\/978-3-540-39624-6_14"},{"key":"9505_CR54","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/j.neunet.2008.11.005","volume":"22","author":"Z Xu","year":"2009","unstructured":"Xu, Z., Huang, K., Zhu, J., King, I., Lyu, M.R.: A novel kernel-based maximum a posteriori classification method. Neural Netw. 22, 977\u2013987 (2009)","journal-title":"Neural Netw."}],"container-title":["Statistics and Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11222-014-9505-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11222-014-9505-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11222-014-9505-x","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T12:52:36Z","timestamp":1746363156000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11222-014-9505-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9,4]]},"references-count":54,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2015,11]]}},"alternative-id":["9505"],"URL":"https:\/\/doi.org\/10.1007\/s11222-014-9505-x","relation":{},"ISSN":["0960-3174","1573-1375"],"issn-type":[{"value":"0960-3174","type":"print"},{"value":"1573-1375","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,9,4]]}}}