{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:04:54Z","timestamp":1761059094819},"publisher-location":"Berlin, Heidelberg","reference-count":24,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540244578"},{"type":"electronic","value":"9783540305606"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2005]]},"DOI":"10.1007\/978-3-540-30560-6_4","type":"book-chapter","created":{"date-parts":[[2010,7,2]],"date-time":"2010-07-02T17:39:25Z","timestamp":1278092365000},"page":"98-127","source":"Crossref","is-referenced-by-count":11,"title":["Analysis of Some Methods for Reduced Rank Gaussian Process Regression"],"prefix":"10.1007","author":[{"given":"Joaquin","family":"Qui\u00f1onero-Candela","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carl Edward","family":"Rasmussen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"4_CR1","doi-asserted-by":"crossref","DOI":"10.1002\/9781119115151","volume-title":"Statistics for Spatial Data","author":"N.A.C. Cressie","year":"1993","unstructured":"Cressie, N.A.C.: Statistics for Spatial Data. John Wiley and Sons, New Jersey (1993)"},{"key":"4_CR2","unstructured":"Csat\u00f3, L.: Gaussian Processes \u2013 Iterative Sparse Approximation. PhD thesis, Aston University, Birmingham, United Kingdom (2002)"},{"issue":"3","key":"4_CR3","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1162\/089976602317250933","volume":"14","author":"L. Csat\u00f3","year":"2002","unstructured":"Csat\u00f3, L., Opper, M.: Sparse online gaussian processes. Neural Computation\u00a014(3), 641\u2013669 (2002)","journal-title":"Neural Computation"},{"key":"4_CR4","unstructured":"Gibbs, M., MacKay, D.J.C.: Efficient implementation of gaussian processes. Technical report, Cavendish Laboratory, Cambridge University, Cambridge, United Kingdom (1997)"},{"key":"4_CR5","first-page":"609","volume-title":"Neural Information Processing Systems","author":"N. Lawrence","year":"2003","unstructured":"Lawrence, N., Seeger, M., Herbrich, R.: Fast sparse gaussian process methods: The informative vector machine. In: Becker, S., Thrun, S., Obermayer, K. (eds.) Neural Information Processing Systems, vol.\u00a015, pp. 609\u2013616. MIT Press, Cambridge (2003)"},{"issue":"2","key":"4_CR6","first-page":"1053","volume":"100","author":"D.J.C. MacKay","year":"1994","unstructured":"MacKay, D.J.C.: Bayesian non-linear modelling for the energy prediction competition. ASHRAE Transactions\u00a0100(2), 1053\u20131062 (1994)","journal-title":"ASHRAE Transactions"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Cressie, N.A.C.: Statistics for Spatial Data. John Wiley and Sons, New Jersey (1993)","DOI":"10.1002\/9781119115151"},{"key":"4_CR8","series-title":"Lecture Notes in Statistics","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4612-0745-0","volume-title":"Bayesian Learning for Neural Networks","author":"R.M. Neal","year":"1996","unstructured":"Neal, R.M.: Bayesian Learning for Neural Networks. Lecture Notes in Statistics, vol.\u00a0118. Springer, Heidelberg (1996)"},{"key":"4_CR9","volume-title":"Numerical Recipes in C","author":"W. Press","year":"1992","unstructured":"Press, W., Flannery, B., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C, 2nd edn. Cambridge University Press, Cambridge (1992)","edition":"2"},{"key":"4_CR10","unstructured":"Rasmussen, C.E.: Evaluation of Gaussian Processes and Other Methods for Non-linear Regression. PhD thesis, Department of Computer Science, University of Toronto, Toronto, Ontario (1996)"},{"key":"4_CR11","unstructured":"Rasmussen, C.E.: Reduced rank gaussian process learning. Unpublished Manuscript (2002)"},{"key":"4_CR12","volume-title":"Learning with Kernels","author":"B. Sch\u00f6lkopf","year":"2002","unstructured":"Sch\u00f6lkopf, B., Smola, A.J.: Learning with Kernels. MIT Press, Cambridge (2002)"},{"key":"4_CR13","first-page":"953","volume-title":"Advances in Neural Information Processing Systems","author":"A. Schwaighofer","year":"2003","unstructured":"Schwaighofer, A., Tresp, V.: Transductive and inductive methods for approximate gaussian process regression. In: Becker, S., Thrun, S., Obermayer, K. (eds.) Advances in Neural Information Processing Systems, vol.\u00a015, pp. 953\u2013960. MIT Press, Cambridge (2003)"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Seeger, M.: Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error Bounds and Sparse Approximations. PhD thesis, University of Edinburgh, Edinburgh, Scotland (2003)","DOI":"10.1162\/153244303765208386"},{"key":"4_CR15","unstructured":"Seeger, M., Williams, C., Lawrence, N.: Fast forward selection to speed up sparse gaussian process regression. In: Bishop, C.M., Frey, B.J. (eds.) Ninth International Workshop on Artificial Intelligence and Statistics, Society for Artificial Intelligence and Statistics (2003)"},{"key":"4_CR16","first-page":"619","volume-title":"Advances in Neural Information Processing Systems","author":"A.J. Smola","year":"2001","unstructured":"Smola, A.J., Bartlett, P.L.: Sparse greedy Gaussian process regression. In: Leen, T.K., Dietterich, T.G., Tresp, V. (eds.) Advances in Neural Information Processing Systems, vol.\u00a013, pp. 619\u2013625. MIT Press, Cambridge (2001)"},{"key":"4_CR17","first-page":"911","volume-title":"International Conference on Machine Learning","author":"A.J. Smola","year":"2000","unstructured":"Smola, A.J., Sch\u00f6lkopf, B.: Sparse greedy matrix approximation for machine learning. In: Langley, P. (ed.) International Conference on Machine Learning, vol.\u00a017, pp. 911\u2013918. Morgan Kaufmann, San Francisco (2000)"},{"key":"4_CR18","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1162\/15324430152748236","volume":"1","author":"M.E. Tipping","year":"2001","unstructured":"Tipping, M.E.: Sparse bayesian learning and the relevance vector machine. Journal of Machine Learning Research\u00a01, 211\u2013244 (2001)","journal-title":"Journal of Machine Learning Research"},{"issue":"11","key":"4_CR19","doi-asserted-by":"publisher","first-page":"2719","DOI":"10.1162\/089976600300014908","volume":"12","author":"V. Tresp","year":"2000","unstructured":"Tresp, V.: A bayesian committee machine. Neural Computation\u00a012(11), 2719\u20132741 (2000)","journal-title":"Neural Computation"},{"key":"4_CR20","first-page":"620","volume-title":"Advances in Neural Information Processing Systems","author":"G. Wahba","year":"1999","unstructured":"Wahba, G., Lin, X., Gao, F., Xiang, D., Klein, R., Klein, B.: The biasvariance tradeoff and the randomized GACV. In: Kerns, M.S., Solla, S.A., Cohn, D.A. (eds.) Advances in Neural Information Processing Systems, vol.\u00a011, pp. 620\u2013626. MIT Press, Cambridge (1999)"},{"key":"4_CR21","first-page":"295","volume-title":"Advances in Neural Information Processing Systems","author":"C. Williams","year":"1997","unstructured":"Williams, C.: Computation with infinite neural networks. In: Mozer, M.C., Jordan, M.I., Petsche, T. (eds.) Advances in Neural Information Processing Systems, vol.\u00a09, pp. 295\u2013301. MIT Press, Cambridge (1997a)"},{"key":"4_CR22","unstructured":"Williams, C.: Prediction with gaussian processes: From linear regression to linear prediction and beyond. Technical Report NCRG\/97\/012, Dept of Computer Science and Applied Mathematics, Aston University, Birmingham, United Kingdom (1997b)"},{"key":"4_CR23","unstructured":"Williams, C., Rasmussen, C.E., Schwaighofer, A., Tresp, V.: Observations of the nystr\u00f6m method for gaussiam process prediction. Technical report, University of Edinburgh, Edinburgh, Scotland (2002)"},{"key":"4_CR24","first-page":"682","volume-title":"Advances in Neural Information Processing Systems","author":"C. Williams","year":"2001","unstructured":"Williams, C., Seeger, M.: Using the Nystr\u00f6m method to speed up kernel machines. In: Leen, T.K., Dietterich, T.G., Tresp, V. (eds.) Advances in Neural Information Processing Systems, vol.\u00a013, pp. 682\u2013688. MIT Press, Cambridge (2001)"}],"container-title":["Lecture Notes in Computer Science","Switching and Learning in Feedback Systems"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-30560-6_4.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T00:09:20Z","timestamp":1711584560000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-30560-6_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005]]},"ISBN":["9783540244578","9783540305606"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-30560-6_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2005]]}}}