Joaquin Quiñonero Candela

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Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Ralf HerbrichZalandoVerified email at zalando.de
Thore GraepelResearch Scientist, Google DeepMind, and Professor of Computer Science, UCLVerified email at ucl.ac.uk
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing ScienceVerified email at glasgow.ac.uk
Patrice SimardMicrosoft ResearchVerified email at microsoft.com
Denis CharlesMicrosoft ResearchVerified email at microsoft.com
Miguel Lázaro-GredillaDirector of research, Vicarious AIVerified email at vicarious.com
Fabian SinzGroup Leader, University TübingenVerified email at uni-tuebingen.de
Jan LarsenTechnical University of Denmark, DTU ComputeVerified email at dtu.dk
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
Ido DaganProfessor, Computer Science Department, Bar-Ilan UniversityVerified email at cs.biu.ac.il
Bernardo MagniniResearcher, Fondazone Bruno Kessler - FBK, Trento, ItalyVerified email at fbk.eu
Ole WintherBiology, Univ of Copenhagen, Genomic Medicine, Rigshospitalet and Technical University of DenmarkVerified email at bio.ku.dk
Florence d'Alché-BucTélécom Paris, Institut Polytechnique de ParisVerified email at telecom-paris.fr
Leon BottouFacebook AI ResearchVerified email at bottou.org
Jonas PetersProfessor of Statistics, University of CopenhagenVerified email at math.ku.dk

Joaquin Quiñonero Candela

Engineering Director at Facebook

Verified email at fb.com - Homepage

Machine Learning Bayesian Inference


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A unifying view of sparse approximate Gaussian process regression J Quinonero-Candela, CE Rasmussen The Journal of Machine Learning Research 6, 1939-1959, 2005	1590	2005
Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009	918	2009
Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009	853	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	538	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	510	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	487*	2003
Counterfactual reasoning and learning systems: The example of computational advertising D Charles, M Chickering, P Simard Journal of Machine Learning Research 14, 2013	394	2013
Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... Journal of Machine Learning Research 11 (Jun), 1865-1881, 2010	368	2010
Local distance preservation in the GP-LVM through back constraints ND Lawrence, J Quinonero-Candela Proceedings of the 23rd international conference on Machine learning, 513-520, 2006	259	2006
When training and test sets are different: characterizing learning transfer A Storkey Dataset shift in machine learning 30, 3-28, 2009	195	2009
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	166*	2003
Approximation methods for gaussian process regression J Quiñonero-Candela, CE Rasmussen, CKI Williams Large-scale kernel machines, 203-224, 2007	155	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	97	2005
Event Prediction R Herbrich, T Graepel, O Zoeter, JQ Candela, P Trelford US Patent App. 11/835,985, 2009	91	2009
Learning with uncertainty-Gaussian processes and relevance vector machines J Quiñonero-Candela	73*	2004
Evaluating predictive uncertainty challenge J Quiñonero-Candela, C Rasmussen, F Sinz, O Bousquet, B Schölkopf Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual …, 2006	72	2006
Event prediction in dynamic environments T Graepel, JQ Candela, TI Borchert, R Herbrich US Patent 8,417,650, 2013	70	2013
Learning depth from stereo F Sinz, J Quiñonero-Candela, G Bakır, C Rasmussen, M Franz Pattern Recognition, 245-252, 2004	60	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	56	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	52	2003

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