{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T16:52:19Z","timestamp":1780073539168,"version":"3.54.0"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2016,12,30]],"date-time":"2016-12-30T00:00:00Z","timestamp":1483056000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["292334"],"award-info":[{"award-number":["292334"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["294238"],"award-info":[{"award-number":["294238"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["295503"],"award-info":[{"award-number":["295503"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["Center of Excellence in Computational Inference COIN"],"award-info":[{"award-number":["Center of Excellence in Computational Inference COIN"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["268874"],"award-info":[{"award-number":["268874"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["295503"],"award-info":[{"award-number":["295503"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"crossref","award":["295496"],"award-info":[{"award-number":["295496"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Finnish Funding Agency for Innovation Tekes","award":["40128\/14"],"award-info":[{"award-number":["40128\/14"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2017,5]]},"DOI":"10.1007\/s10994-016-5618-0","type":"journal-article","created":{"date-parts":[[2016,12,30]],"date-time":"2016-12-30T21:20:03Z","timestamp":1483132803000},"page":"713-739","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Multi-view kernel completion"],"prefix":"10.1007","volume":"106","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7453-9880","authenticated-orcid":false,"given":"Sahely","family":"Bhadra","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1925-9154","authenticated-orcid":false,"given":"Samuel","family":"Kaski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0705-4314","authenticated-orcid":false,"given":"Juho","family":"Rousu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2016,12,30]]},"reference":[{"key":"5618_CR1","first-page":"28","volume":"22","author":"M Amini","year":"2009","unstructured":"Amini, M., Usunier, N., & Goutte, C. (2009). Learning from multiple partially observed views\u2014An application to multilingual text categorization. Advances in Neural Information Processing Systems, 22, 28\u201336.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"5618_CR2","doi-asserted-by":"crossref","unstructured":"Argyriou, A., Micchelli, C.A., & Pontil, M. (2005). Learning convex combinations of continuously parameterized basic kernels. In Proceedings of the 18th annual conference on learning theory (pp. 338\u2013352).","DOI":"10.1007\/11503415_23"},{"key":"5618_CR3","first-page":"41","volume":"19","author":"A Argyriou","year":"2006","unstructured":"Argyriou, A., Evgeniou, T., & Pontil, M. (2006). Multi-task feature learning. Advances in Neural Information Processing Systems, 19, 41\u201348.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"5618_CR4","doi-asserted-by":"crossref","unstructured":"Bach, F., Lanckriet, G., & Jordan, M. (2004). Multiple kernel learning, conic duality, and the SMO algorithm. In Proceedings of the 21st international conference on machine learning (pp. 6\u201313). ACM.","DOI":"10.1145\/1015330.1015424"},{"key":"5618_CR5","doi-asserted-by":"crossref","unstructured":"Bach, F., Jenatton, R., Mairal, J., & Obozinski, G. (2011). Convex optimization with sparsity-inducing norms. Optimization for Machine Learning, 5, pp. 19\u201353.","DOI":"10.7551\/mitpress\/8996.003.0004"},{"key":"5618_CR6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-9-12","volume":"9","author":"G Brock","year":"2008","unstructured":"Brock, G., Shaffer, J., Blakesley, R., Lotz, M., & Tseng, G. (2008). Which missing value imputation method to use in expression profiles: A comparative study and two selection schemes. BMC Bioinformatics, 9, 1\u201312.","journal-title":"BMC Bioinformatics"},{"key":"5618_CR7","first-page":"795","volume":"13","author":"C Cortes","year":"2012","unstructured":"Cortes, C., Mohri, M., & Rostamizadeh, A. (2012). Algorithms for learning kernels based on centered alignment. Journal of Machine Learning Research, 13, 795\u2013828.","journal-title":"Journal of Machine Learning Research"},{"issue":"2\u20133","key":"5618_CR8","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1023\/A:1013625426931","volume":"18","author":"N Cristianini","year":"2002","unstructured":"Cristianini, N., Shawe-Taylor, J., & Lodhi, H. (2002). Latent semantic kernels. Journal of Intelligent Information Systems, 18(2\u20133), 127\u2013152.","journal-title":"Journal of Intelligent Information Systems"},{"issue":"10","key":"5618_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/gb-2013-14-10-r110","volume":"14","author":"A Daemen","year":"2013","unstructured":"Daemen, A., Griffith, O., Heiser, L., et al. (2013). Modeling precision treatment of breast cancer. Genome Biology, 14(10), 1.","journal-title":"Genome Biology"},{"key":"5618_CR10","first-page":"2211","volume":"12","author":"M G\u00f6nen","year":"2011","unstructured":"G\u00f6nen, M., & Alpaydin, E. (2011). Multiple kernel learning algorithms. Journal of Machine Learning Research, 12, 2211\u20132268.","journal-title":"Journal of Machine Learning Research"},{"key":"5618_CR11","doi-asserted-by":"crossref","unstructured":"Graepel, T. (2002). Kernel matrix completion by semidefinite programming. In Proceedings of the 12th international conference on artificial neural networks, Springer (pp. 694\u2013699).","DOI":"10.1007\/3-540-46084-5_113"},{"issue":"8","key":"5618_CR12","doi-asserted-by":"crossref","first-page":"2724","DOI":"10.1073\/pnas.1018854108","volume":"109","author":"LM Heiser","year":"2012","unstructured":"Heiser, L. M., Sadanandam, A., et al. (2012). Subtype and pathway specific responses to anticancer compounds in breast cancer. Proceedings of the National Academy of Sciences, 109(8), 2724\u20132729.","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"5618_CR13","doi-asserted-by":"crossref","unstructured":"Kumar, S., Mohri, M., & Talwalkar, A. (2009). On sampling-based approximate spectral decomposition. In Proceedings of the 26th annual international conference on machine learning (pp. 53\u2013560). ACM.","DOI":"10.1145\/1553374.1553446"},{"key":"5618_CR14","doi-asserted-by":"crossref","unstructured":"Lian, W., Rai, P., Salazar, E., & Carin, L. (2015). Integrating features and similarities: Flexible models for heterogeneous multiview data. In Proceedings of the 29th AAAI conference on artificial intelligence (pp. 2757\u20132763).","DOI":"10.1609\/aaai.v29i1.9549"},{"key":"5618_CR15","doi-asserted-by":"crossref","unstructured":"Paisley, J., Carin, & L. (2010). A nonparametric Bayesian model for kernel matrix completion. In The 35th international conference on acoustics, speech, and signal processing, IEEE (pp. 2090\u20132093).","DOI":"10.1109\/ICASSP.2010.5495105"},{"issue":"5500","key":"5618_CR16","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"ST Roweis","year":"2000","unstructured":"Roweis, S. T., & Saul, L. K. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500), 2323\u20132326.","journal-title":"Science"},{"key":"5618_CR17","doi-asserted-by":"crossref","unstructured":"Shao, W., Shi, X., & Yu, P.S. (2013). Clustering on multiple incomplete datasets via collective kernel learning. In IEEE 13th international conference on, data mining (ICDM), 2013 (pp. 1181\u20131186). IEEE.","DOI":"10.1109\/ICDM.2013.117"},{"key":"5618_CR18","unstructured":"Trivedi, A., Rai, P., Daum\u00e9\u00a0III, H., & DuVall, S.L. (2005). Multiview clustering with incomplete views. In Proceedings of the NIPS workshop."},{"key":"5618_CR19","first-page":"67","volume":"4","author":"K Tsuda","year":"2003","unstructured":"Tsuda, K., Akaho, S., & Asai, K. (2003). The em algorithm for kernel matrix completion with auxiliary data. The Journal of Machine Learning Research, 4, 67\u201381.","journal-title":"The Journal of Machine Learning Research"},{"key":"5618_CR20","doi-asserted-by":"crossref","unstructured":"Wang, P., Shen, C., & Van Den\u00a0Hengel, A. (2013). A fast semidefinite approach to solving binary quadratic problems. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1312\u20131319).","DOI":"10.1109\/CVPR.2013.173"},{"key":"5618_CR21","unstructured":"Williams, C., Seeger, M. (2001). Using the nystr\u00f6m method to speed up kernel machines. In Proceedings of the 14th annual conference on neural information processing systems, EPFL-CONF-161322 (pp. 682\u2013688)."},{"key":"5618_CR22","unstructured":"Williams, D., Carin, L. (2005). Analytical kernel matrix completion with incomplete multi-view data. In Proceedings of the ICML workshop on learning with multiple views."},{"key":"5618_CR23","unstructured":"Xu, M., Jin, R., & Zhou, Z.H. (2013). Speedup matrix completion with side information: Application to multi-label learning. In Advances in neural information processing systems (pp. 2301\u20132309)."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-016-5618-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-016-5618-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-016-5618-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T14:14:42Z","timestamp":1692627282000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-016-5618-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,30]]},"references-count":23,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2017,5]]}},"alternative-id":["5618"],"URL":"https:\/\/doi.org\/10.1007\/s10994-016-5618-0","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,12,30]]}}}