| A unifying view of sparse approximate Gaussian process regression J Quiñonero-Candela, CE Rasmussen Journal of Machine Learning Research 6 (Dec), 1939-1959, 2005 | 1516 | 2005 |
| Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009 | 878 | 2009 |
| Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009 | 822 | 2009 |
| Web-scale Bayesian click-through rate prediction for sponsored search advertising in Microsoft’s Bing search engine T Graepel, J Quiñonero-Candela, T Borchert, R Herbrich Proc. 27th Internat. Conf. on Machine Learning. Morgan Kaufmann, San …, 2010 | 531 | 2010 |
| Practical lessons from predicting clicks on ads at facebook X He, J Pan, O Jin, T Xu, B Liu, T Xu, Y Shi, A Atallah, R Herbrich, ... Proceedings of the Eighth International Workshop on Data Mining for Online …, 2014 | 493 | 2014 |
| Gaussian Process priors with uncertain inputs -- Application to multiple-step ahead time series forecasting A Girard, CE Rasmussen, J Quiñonero-Candela, R Murray-Smith MIT Press, 2003 | 481* | 2003 |
| Counterfactual reasoning and learning systems: The example of computational advertising L Bottou, J Peters, J Quiñonero-Candela, DX Charles, DM Chickering, ... The Journal of Machine Learning Research 14 (1), 3207-3260, 2013 | 383 | 2013 |
| Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... Journal of Machine Learning Research 11 (Jun), 1865-1881, 2010 | 357 | 2010 |
| Local distance preservation in the GP-LVM through back constraints ND Lawrence, J Quiñonero-Candela Proceedings of the 23rd international conference on Machine learning, 513-520, 2006 | 247 | 2006 |
| Propagation of uncertainty in Bayesian kernel models-application to multiple-step ahead forecasting J Quiñonero-Candela, A Girard, J Larsen, CE Rasmussen Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03 …, 2003 | 161* | 2003 |
| Approximation methods for gaussian process regression J Quiñonero-Candela, CE Rasmussen, CKI Williams Large-scale kernel machines, 203-224, 2007 | 148 | 2007 |
| Healing the relevance vector machine through augmentation CE Rasmussen, J Quiñonero-Candela Proceedings of the 22nd international conference on Machine learning, 689-696, 2005 | 95 | 2005 |
| Event Prediction R Herbrich, T Graepel, O Zoeter, JQ Candela, P Trelford US Patent App. 11/835,985, 2009 | 90 | 2009 |
| Evaluating predictive uncertainty challenge J Quiñonero-Candela, C Rasmussen, F Sinz, O Bousquet, B Schölkopf Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual …, 2006 | 74 | 2006 |
| Learning with uncertainty-Gaussian processes and relevance vector machines J Quiñonero-Candela | 73* | 2004 |
| Event prediction in dynamic environments T Graepel, JQ Candela, TI Borchert, R Herbrich US Patent 8,417,650, 2013 | 68 | 2013 |
| Learning depth from stereo F Sinz, J Quiñonero-Candela, G Bakır, C Rasmussen, M Franz Pattern Recognition, 245-252, 2004 | 56 | 2004 |
| Time series prediction based on the relevance vector machine with adaptive kernels J Quiñonero-Candela, LK Hansen Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International …, 2002 | 54 | 2002 |
| Prediction at an uncertain input for Gaussian processes and relevance vector machines-application to multiple-step ahead time-series forecasting J Quinonero-Candela, A Girard, CE Rasmussen Technical University of Denmark, DTU: Informatics and Mathematical Modelling, 2003 | 51 | 2003 |
| Scalable clustering A Schwaighofer, JQ Candela, T Borchert, T Graepel, R Herbrich US Patent 8,204,838, 2012 | 36 | 2012 |
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeBekræftet mail på cam.ac.uk
