%0 Conference Paper %1 yu_learning_2005 %A Yu, Kai %A Tresp, Volker %A Schwaighofer, Anton %B Proceedings of the 22nd international conference on Machine learning %C Bonn, Germany %D 2005 %I ACM %K %P 1012-1019 %R 10.1145/1102351.1102479 %T Learning Gaussian processes from multiple tasks %U http://portal.acm.org/citation.cfm?id=1102479&dl=GUIDE&coll=GUIDE&CFID=69344422&CFTOKEN=94303924 %X We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equivalence between parametric linear models and nonparametric Gaussian processes (GPs). The resulting models can be learned easily via an EM-algorithm. Empirical studies on multi-label text categorization suggest that the presented models allow accurate solutions of these multi-task problems. %@ 1-59593-180-5

@inproceedings{yu_learning_2005, abstract = {We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equivalence between parametric linear models and nonparametric Gaussian processes (GPs). The resulting models can be learned easily via an EM-algorithm. Empirical studies on multi-label text categorization suggest that the presented models allow accurate solutions of these multi-task problems.}, added-at = {2009-03-05T08:50:36.000+0100}, address = {Bonn, Germany}, author = {Yu, Kai and Tresp, Volker and Schwaighofer, Anton}, biburl = {https://www.bibsonomy.org/bibtex/2db96238c10869835cab8ad79f44b8d45/bcao}, booktitle = {Proceedings of the 22nd international conference on Machine learning}, doi = {10.1145/1102351.1102479}, interhash = {a3dcc2f9502736d2349eca4ccc556357}, intrahash = {db96238c10869835cab8ad79f44b8d45}, isbn = {1-59593-180-5}, keywords = {}, pages = {1012-1019}, publisher = {ACM}, timestamp = {2009-03-05T08:50:36.000+0100}, title = {Learning Gaussian processes from multiple tasks}, url = {http://portal.acm.org/citation.cfm?id=1102479\&dl=GUIDE\&coll=GUIDE\&CFID=69344422\&CFTOKEN=94303924}, year = 2005 }