{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T04:20:45Z","timestamp":1745382045397,"version":"3.40.4"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2012,11,1]],"date-time":"2012-11-01T00:00:00Z","timestamp":1351728000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Comput. Sci. Technol."],"published-print":{"date-parts":[[2012,11]]},"DOI":"10.1007\/s11390-012-1305-1","type":"journal-article","created":{"date-parts":[[2012,11,29]],"date-time":"2012-11-29T17:02:51Z","timestamp":1354208571000},"page":"1289-1301","source":"Crossref","is-referenced-by-count":0,"title":["A Kernel Approach to Multi-Task Learning with Task-Specific Kernels"],"prefix":"10.1007","volume":"27","author":[{"given":"Wei","family":"Wu","sequence":"first","affiliation":[]},{"given":"Hang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yun-Hua","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Rong","family":"Jin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,11,15]]},"reference":[{"issue":"1","key":"1305_CR1","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1023\/A:1007379606734","volume":"28","author":"R Caruana","year":"1997","unstructured":"Caruana R (1997) Multitask learning. Machine Learning 28(1):41\u201375","journal-title":"Machine Learning"},{"key":"1305_CR2","doi-asserted-by":"crossref","unstructured":"Ben-David S, Schuller R. Exploiting task relatedness for multiple task learning. In Lecture Notes in Computer Science, Carbonell J, Siekmann J (eds.), Springer, 2003, pp.567\u2013580.","DOI":"10.1007\/978-3-540-45167-9_41"},{"issue":"April","key":"1305_CR3","first-page":"615","volume":"6","author":"T Evgeniou","year":"2005","unstructured":"Evgeniou T, Micchelli C, Pontil M (2005) Learning multiple tasks with kernel methods. Journal of Machine Learning Research 6(April):615\u2013637","journal-title":"Journal of Machine Learning Research"},{"key":"1305_CR4","unstructured":"Kato T, Kashima H, Sugiyama M, Asai K. Multi-task learning via conic programming. In Proc. the 22nd Conf. Neural Information Processing System, Dec. 2008, pp.737\u2013744."},{"key":"1305_CR5","doi-asserted-by":"crossref","unstructured":"Evgeniou T, Pontil M. Regularized multi-task learning. In Proc. the 10th SIGKDD, Aug. 2004, pp.109\u2013117.","DOI":"10.1145\/1014052.1014067"},{"key":"1305_CR6","unstructured":"Micchelli C, Pontil M. Kernels for multi-task learning. In Proc. the 19th NIPS, Dec. 2005, pp.921\u2013928."},{"issue":"Nov.","key":"1305_CR7","first-page":"1817","volume":"6","author":"RK Ando","year":"2005","unstructured":"Ando RK, Zhang T (2005) A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research 6(Nov.):1817\u20131853","journal-title":"Journal of Machine Learning Research"},{"key":"1305_CR8","doi-asserted-by":"crossref","unstructured":"Argyriou A, Evgeniou T, Pontil M. Multi-task feature learning. In Proc. NIPS, December 2007, pp.41\u201348.","DOI":"10.2139\/ssrn.1031158"},{"key":"1305_CR9","volume-title":"Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond","author":"B Sch\u00f6lkopf","year":"2002","unstructured":"Sch\u00f6lkopf B, Smola A (2002) Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge, Massachusetts, USA"},{"issue":"3","key":"1305_CR10","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 (2008) Kernel methods in machine learning. Annals of Statistics 36(3):1171\u20131220","journal-title":"Annals of Statistics"},{"key":"1305_CR11","unstructured":"Lanckriet G R, Cristianini N, Bartlett P, Ghaoui L, Jordan M. Learning the kernel matrix with semi-definite programming. In Proc. the 19th ICML, July 2002, pp.323\u2013330."},{"key":"1305_CR12","doi-asserted-by":"crossref","unstructured":"Bach F, Lanckriet G R, Jordan M. Multiple kernel learning, conic duality, and the SMO algorithm. In Proc. the 21st ICML, July 2004, Article No. 6.","DOI":"10.1145\/1015330.1015424"},{"key":"1305_CR13","unstructured":"Tang L, Chen J, Ye J. On multiple kernel learning with multiple labels. In Proc. the 21st IJCAI, July 2009, pp.1255\u20131260."},{"key":"1305_CR14","unstructured":"Ji S, Sun L, Jin R, Ye J. Multi-label multiple kernel learning. In Proc. the 22nd NIPS, 2008, pp.777\u2013784"},{"key":"1305_CR15","doi-asserted-by":"crossref","unstructured":"Duan L, Tsang I, Xu D, Chua T. Domain adaptation from multiple sources via auxiliary classifiers. In Proc. the 26th ICML, June 2009, pp.289\u2013296.","DOI":"10.1145\/1553374.1553411"},{"issue":"3","key":"1305_CR16","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1090\/S0002-9947-1950-0051437-7","volume":"68","author":"N Aronszajn","year":"1950","unstructured":"Aronszajn N (1950) Theory of reproducting kernels. Transactions of the American Mathematical Society 68(3):337\u2013404","journal-title":"Transactions of the American Mathematical Society"},{"issue":"1","key":"1305_CR17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1090\/S0273-0979-01-00923-5","volume":"39","author":"F Cucker","year":"2002","unstructured":"Cucker F, Smale S (2002) On the mathematical foundations of learning. Bulletin of the American Mathematical Society 39(1):1\u201349","journal-title":"Bulletin of the American Mathematical Society"},{"key":"1305_CR18","volume-title":"An Introduction to Partial Differential Equations","author":"M Renardy","year":"1993","unstructured":"Renardy M, Rogers R (1993) An Introduction to Partial Differential Equations. Springer-Verlag, New York, USA"},{"key":"1305_CR19","doi-asserted-by":"crossref","unstructured":"Elisseeff A, Weston J. Kernel methods for multi-labelled classification and categorical regression problems. In Proc. the 16th NIPS, December 2002, pp.681\u2013688.","DOI":"10.7551\/mitpress\/1120.003.0092"},{"key":"1305_CR20","doi-asserted-by":"crossref","unstructured":"Lewis D. Evaluating text categorization. In Proc. the Work-shop on Speech and Natural Language, Feb. 1991, pp.312\u2013318.","DOI":"10.3115\/112405.112471"},{"key":"1305_CR21","doi-asserted-by":"crossref","unstructured":"Lanckriet G R, Deng M, Cristianini N, Jordan M, Noble W. Kernel-based data fusion and its application to protein function prediction in yeast. In Proc. Pacific Symp. Biocomputing, January 2004, pp.300\u2013311.","DOI":"10.1142\/9789812704856_0029"},{"key":"1305_CR22","volume-title":"Foundations of Modern Analysis","author":"J Dieudonn\u00e9","year":"1969","unstructured":"Dieudonn\u00e9 J (1969) Foundations of Modern Analysis, 2nd edn. Academic Press, New York, USA","edition":"2"},{"issue":"Nov.","key":"1305_CR23","first-page":"2399","volume":"7","author":"M Belkin","year":"2006","unstructured":"Belkin M, Niyogi P, Sindhwani V (2006) Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research 7(Nov.):2399\u20132434","journal-title":"Journal of Machine Learning Research"},{"issue":"Nov.","key":"1305_CR24","first-page":"463","volume":"3","author":"P Bartlett","year":"2002","unstructured":"Bartlett P, Mendelson S (2002) Rademacher and Gaussian complexities: Risk bounds and structural results. Journal of Machine Learning Research 3(Nov.):463\u2013482","journal-title":"Journal of Machine Learning Research"}],"container-title":["Journal of Computer Science and Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-012-1305-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11390-012-1305-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-012-1305-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T23:52:37Z","timestamp":1745365957000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11390-012-1305-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,11]]},"references-count":24,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2012,11]]}},"alternative-id":["1305"],"URL":"https:\/\/doi.org\/10.1007\/s11390-012-1305-1","relation":{},"ISSN":["1000-9000","1860-4749"],"issn-type":[{"type":"print","value":"1000-9000"},{"type":"electronic","value":"1860-4749"}],"subject":[],"published":{"date-parts":[[2012,11]]}}}