{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:19:09Z","timestamp":1740122349573,"version":"3.37.3"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"S6","license":[{"start":{"date-parts":[[2018,3,16]],"date-time":"2018-03-16T00:00:00Z","timestamp":1521158400000},"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":["Cluster Comput"],"published-print":{"date-parts":[[2019,11]]},"DOI":"10.1007\/s10586-018-2106-2","type":"journal-article","created":{"date-parts":[[2018,3,15]],"date-time":"2018-03-15T23:15:16Z","timestamp":1521155716000},"page":"13843-13851","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Manifold regularized multiple kernel learning with Hellinger distance"],"prefix":"10.1007","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4418-5185","authenticated-orcid":false,"given":"Tao","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongmei","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaogang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kamil","family":"\u0158\u00edha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,3,16]]},"reference":[{"issue":"1","key":"2106_CR1","first-page":"71","volume":"200","author":"MN Murty","year":"2015","unstructured":"Murty, M.N., Devi, V.S.: Introduction to pattern recognition and machine learning. J. Cell. Physiol. 200(1), 71\u201381 (2015)","journal-title":"J. Cell. Physiol."},{"issue":"7","key":"2106_CR2","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2014","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527\u20131554 (2014)","journal-title":"Neural Comput."},{"issue":"17","key":"2106_CR3","doi-asserted-by":"publisher","first-page":"4013","DOI":"10.1002\/sec.1584","volume":"9","author":"J Sheu","year":"2016","unstructured":"Sheu, J., Chen, Y., Chu, K., et al.: An intelligent three-phase spam filtering method based on decision tree data mining. Secur. Commun. Netw. 9(17), 4013\u20134026 (2016)","journal-title":"Secur. Commun. Netw."},{"issue":"3","key":"2106_CR4","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1007\/s10618-013-0311-4","volume":"27","author":"B Campello","year":"2013","unstructured":"Campello, B., Moulavi, D., Zimek, A., Sander, J.: A framework for semisupervised and unsupervised optimal extraction of clusters from hierarchies. Data Min. Knowl. Discov. 27(3), 344\u2013371 (2013)","journal-title":"Data Min. Knowl. Discov."},{"issue":"4","key":"2106_CR5","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1017\/S0143385712000260","volume":"33","author":"APW S\u00f8rensen","year":"2013","unstructured":"S\u00f8rensen, A.P.W.: Geometric classification of simple graph algebras. Ergod. Theory Dyn. Syst. 33(4), 1199\u20131220 (2013)","journal-title":"Ergod. Theory Dyn. Syst."},{"key":"2106_CR6","first-page":"544","volume":"161","author":"A Criminisi","year":"2013","unstructured":"Criminisi, A., Shotton, J.: Semi-supervised classification forests. Adv. Comput. Vis. Pattern Recognit. 161, 544\u2013563 (2013)","journal-title":"Adv. Comput. Vis. Pattern Recognit."},{"key":"2106_CR7","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.patcog.2015.10.006","volume":"52","author":"B Wang","year":"2016","unstructured":"Wang, B., Tu, Z., Tsotsos, J.K.: Dynamic label propagation for semi-supervised multi-class multi-label classification. Pattern Recognit. 52, 75\u201385 (2016)","journal-title":"Pattern Recognit."},{"issue":"1","key":"2106_CR8","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 labels and unlabels examples. J. Mach. Learn. Res. 7(1), 2399\u20132434 (2006)","journal-title":"J. Mach. Learn. Res."},{"issue":"16","key":"2106_CR9","doi-asserted-by":"publisher","first-page":"2118","DOI":"10.1016\/j.patrec.2013.08.005","volume":"34","author":"X Xing","year":"2013","unstructured":"Xing, X., Yu, Y., Jiang, H., et al.: A multi-manifold semi-supervised Gaussian mixture model for pattern classification. Pattern Recognit. Lett. 34(16), 2118\u20132125 (2013)","journal-title":"Pattern Recognit. Lett."},{"issue":"1","key":"2106_CR10","first-page":"323","volume":"5","author":"G Lanckriet","year":"2004","unstructured":"Lanckriet, G., Cristianini, N., Bartlett, P., Ghaoui, L.E., Jordan, M.: Learning the kernel matrix with sem-idefinite programming. J. Mach. Learn. Res. 5(1), 323\u2013330 (2004)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"2106_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11063-014-9392-3","volume":"42","author":"Z Liang","year":"2015","unstructured":"Liang, Z., Zhang, L., Liu, J.: A novel multiple kernel learning method based on the Kullback-Leibler divergence. Neural Process. Lett. 42(3), 1\u201318 (2015)","journal-title":"Neural Process. Lett."},{"issue":"7","key":"2106_CR12","doi-asserted-by":"publisher","first-page":"1354","DOI":"10.1109\/TPAMI.2013.212","volume":"36","author":"S Bucak","year":"2014","unstructured":"Bucak, S., Jin, R., Jain, A.K.: Multiple kernel learning for visual object recognition: a review. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1354\u20131369 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"2106_CR13","first-page":"2491","volume":"9","author":"A Rakotomamonjy","year":"2008","unstructured":"Rakotomamonjy, A., Bach, F., Canu, S., Grandvalet, Y.: SimpleMKL. J. Mach. Learn. Res. 9(3), 2491\u20132521 (2008)","journal-title":"J. Mach. Learn. Res."},{"issue":"5","key":"2106_CR14","doi-asserted-by":"publisher","first-page":"1800","DOI":"10.1016\/j.patcog.2013.11.032","volume":"47","author":"S Althloothi","year":"2014","unstructured":"Althloothi, S., Mahoor, M.H., Zhang, X.: Human activity recognition using multi-features and multiple ker-nel learning. Pattern Recognit. 47(5), 1800\u20131812 (2014)","journal-title":"Pattern Recognit."},{"issue":"5","key":"2106_CR15","doi-asserted-by":"publisher","first-page":"1854","DOI":"10.1016\/j.patcog.2014.12.001","volume":"48","author":"A Nazarpour","year":"2015","unstructured":"Nazarpour, A., Adibi, P.: Two-stage multiple kernel learning for supervised dimensionality reduction. Pattern Recognit. 48(5), 1854\u20131862 (2015)","journal-title":"Pattern Recognit."},{"key":"2106_CR16","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.neucom.2014.11.078","volume":"169","author":"F Aiolli","year":"2015","unstructured":"Aiolli, F., Donini, M.: EasyMKL: a scalable multiple kernel learning algorithm. Neurocomputing 169, 215\u2013224 (2015)","journal-title":"Neurocomputing"},{"key":"2106_CR17","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.neucom.2014.03.039","volume":"140","author":"T Yang","year":"2014","unstructured":"Yang, T., Fu, D.: Semi-supervised classification with Laplacian multiple kernel learning. Neurocomputing 140, 19\u201326 (2014)","journal-title":"Neurocomputing"},{"issue":"9","key":"2106_CR18","doi-asserted-by":"publisher","first-page":"1859","DOI":"10.1007\/s11425-012-4438-3","volume":"55","author":"Y Cao","year":"2012","unstructured":"Cao, Y., Chen, D.R.: Generalization errors of Laplacian regularized least squares regression. Sci. China Math. 55(9), 1859\u20131868 (2012)","journal-title":"Sci. China Math."},{"issue":"8","key":"2106_CR19","doi-asserted-by":"publisher","first-page":"3283","DOI":"10.1007\/s00500-015-1707-4","volume":"20","author":"OA Arqub","year":"2016","unstructured":"Arqub, O.A., Al-Smadi, M., Momani, S., et al.: Numerical solutions of fuzzy differential equations using reproducing kernel Hilbert space method. Soft. Comput. 20(8), 3283\u20133302 (2016)","journal-title":"Soft. Comput."},{"issue":"8","key":"2106_CR20","first-page":"491","volume":"12","author":"B Mcfee","year":"2010","unstructured":"Mcfee, B., Lanckriet, G.: Learning multi-modal similarity. J. Mach. Learn. Res. 12(8), 491\u2013523 (2010)","journal-title":"J. Mach. Learn. Res."},{"issue":"8","key":"2106_CR21","first-page":"2467","volume":"8","author":"F Dinuzzo","year":"2007","unstructured":"Dinuzzo, F., Neve, M., Necolao, G.D.: On the representer theorem and equivalent degrees of freedom of SVR. J. Mach. Learn. Res. 8(8), 2467\u20132495 (2007)","journal-title":"J. Mach. Learn. Res."},{"issue":"2","key":"2106_CR22","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1109\/TRA.2004.824649","volume":"20","author":"AM Ladd","year":"2004","unstructured":"Ladd, A.M., Kavraki, L.E.: Measure theoretic analysis of probabilistic path planning. IEEE Trans. Robot. Autom. 20(2), 229\u2013242 (2004)","journal-title":"IEEE Trans. Robot. Autom."},{"issue":"10","key":"2106_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TPDS.2016.2521373","volume":"27","author":"B Chr\u00e9tien","year":"2016","unstructured":"Chr\u00e9tien, B., Escande, A., Kheddar, A.: GPU robot motion planning using semi-infinite nonlinear programming. IEEE Trans. Parallel Distrib. Syst. 27(10), 1\u20131 (2016)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"issue":"06","key":"2106_CR24","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1142\/S0219530516400054","volume":"14","author":"CA Micchelli","year":"2016","unstructured":"Micchelli, C.A., Pontil, M., Wu, Q., et al.: Error bounds for learning the kernel. Anal. Appl. 14(06), 849\u2013868 (2016)","journal-title":"Anal. Appl."},{"issue":"11","key":"2106_CR25","doi-asserted-by":"publisher","first-page":"2858","DOI":"10.1162\/NECO_a_00028","volume":"22","author":"Y Ying","year":"2014","unstructured":"Ying, Y., Campbell, C.: Rademacher chaos complexities for learning the kernel problem. Neural Comput. 22(11), 2858\u20132886 (2014)","journal-title":"Neural Comput."},{"issue":"2","key":"2106_CR26","doi-asserted-by":"publisher","first-page":"113","DOI":"10.14429\/dsj.66.9463","volume":"66","author":"P Ashok","year":"2016","unstructured":"Ashok, P., Nawaz, G.M.K.: Outlier detection method on UCI repository dataset by entropy based rough K-means. Def. Sci. J. 66(2), 113\u2013119 (2016)","journal-title":"Def. Sci. J."},{"issue":"4","key":"2106_CR27","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1109\/TKDE.2015.2507130","volume":"28","author":"D Johnson","year":"2016","unstructured":"Johnson, D., Xiong, C., Corso, J.: Semi-supervised nonlinear distance metric learning via forests of max-margin cluster hierarchies. IEEE Trans. Knowl. Data Eng. 28(4), 1035\u20131046 (2016)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"2106_CR28","first-page":"27","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. Trans. Intell. Syst. Technol. 2, 27\u201327 (2011)","journal-title":"Trans. Intell. Syst. Technol."},{"issue":"4","key":"2106_CR29","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1109\/MSP.2013.2251071","volume":"30","author":"G Ding","year":"2013","unstructured":"Ding, G., Wu, Q., Yao, Y.D., et al.: Kernel-based learning for statistical signal processing in cognitive radio networks: theoretical foundations, example applications, and future directions. IEEE Signal Process. Mag. 30(4), 126\u2013136 (2013)","journal-title":"IEEE Signal Process. Mag."},{"issue":"4","key":"2106_CR30","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/MSP.2013.2253631","volume":"30","author":"Z Harchaoui","year":"2013","unstructured":"Harchaoui, Z., Bach, F., Cappe, O., et al.: Kernel-based methods for hypothesis testing: a unified view. IEEE Signal Process. Mag. 30(4), 87\u201397 (2013)","journal-title":"IEEE Signal Process. Mag."},{"issue":"4","key":"2106_CR31","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/MSP.2013.2253354","volume":"30","author":"JA Bazerque","year":"2013","unstructured":"Bazerque, J.A., Giannakis, G.B.: Nonparametric basis pursuit via sparse kernel-based learning: a unifying view with advances in blind methods. IEEE Signal Process. Mag. 30(4), 112\u2013125 (2013)","journal-title":"IEEE Signal Process. Mag."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-018-2106-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10586-018-2106-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-018-2106-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,26]],"date-time":"2019-11-26T07:24:56Z","timestamp":1574753096000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10586-018-2106-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,16]]},"references-count":31,"journal-issue":{"issue":"S6","published-print":{"date-parts":[[2019,11]]}},"alternative-id":["2106"],"URL":"https:\/\/doi.org\/10.1007\/s10586-018-2106-2","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"type":"print","value":"1386-7857"},{"type":"electronic","value":"1573-7543"}],"subject":[],"published":{"date-parts":[[2018,3,16]]},"assertion":[{"value":"10 August 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 November 2017","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 March 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}