Joaquin Quiñonero Candela - Google Académico

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Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeDirección de correo verificada de cam.ac.uk
Neil D. LawrenceUniversity of CambridgeDirección de correo verificada de cl.cam.ac.uk
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoDirección de correo verificada de k.u-tokyo.ac.jp
Ralf HerbrichZalandoDirección de correo verificada de zalando.de
Thore GraepelResearch Scientist, Google DeepMind, and Professor of Computer Science, UCLDirección de correo verificada de ucl.ac.uk
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing ScienceDirección de correo verificada de glasgow.ac.uk
Leon BottouFacebook AI ResearchDirección de correo verificada de bottou.org
Patrice SimardMicrosoft ResearchDirección de correo verificada de microsoft.com
Jonas PetersProfessor of Statistics, University of CopenhagenDirección de correo verificada de math.ku.dk
Denis CharlesMicrosoft ResearchDirección de correo verificada de microsoft.com
Miguel Lázaro-GredillaSenior researcher, Vicarious AIDirección de correo verificada de vicarious.com
Jan LarsenTechnical University of Denmark, DTU ComputeDirección de correo verificada de dtu.dk
Fabian SinzGroup Leader, University TübingenDirección de correo verificada de uni-tuebingen.de
Chris WilliamsProfessor of Machine Learning, University of EdinburghDirección de correo verificada de inf.ed.ac.uk
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkDirección de correo verificada de dtu.dk
Ido DaganProfessor, Computer Science Department, Bar-Ilan UniversityDirección de correo verificada de cs.biu.ac.il
Bernardo MagniniResearcher, Fondazone Bruno Kessler - FBK, Trento, ItalyDirección de correo verificada de fbk.eu
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedDirección de correo verificada de tuebingen.mpg.de
Ole WintherBiology, Univ of Copenhagen, Genomic Medicine, Rigshospitalet and Technical University of DenmarkDirección de correo verificada de bio.ku.dk
Florence d'Alché-BucInstitut Mines-Télécom / Télécom ParisTechDirección de correo verificada de telecom-paristech.fr

Joaquin Quiñonero Candela

Engineering Director at Facebook

Dirección de correo verificada de fb.com - Página principal

Machine Learning Bayesian Inference


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
A unifying view of sparse approximate Gaussian process regression J Quiñonero-Candela, CE Rasmussen Journal of Machine Learning Research 6 (Dec), 1939-1959, 2005	1410	2005
Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009	766	2009
Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009	714	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	495	2010
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	442*	2003
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	403	2014
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	329	2013
Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... Journal of Machine Learning Research 11 (Jun), 1865-1881, 2010	327	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	237	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	153*	2003
Approximation methods for gaussian process regression J Quiñonero-Candela, CE Rasmussen, CKI Williams Large-scale kernel machines, 203-224, 2007	134	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	90	2005
Event Prediction R Herbrich, T Graepel, O Zoeter, JQ Candela, P Trelford US Patent App. 11/835,985, 2009	88	2009
Learning with uncertainty-Gaussian processes and relevance vector machines J Quiñonero-Candela	69*	2004
Evaluating predictive uncertainty challenge J Quiñonero-Candela, C Rasmussen, F Sinz, O Bousquet, B Schölkopf Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual …, 2006	66	2006
Event prediction in dynamic environments T Graepel, JQ Candela, TI Borchert, R Herbrich US Patent 8,417,650, 2013	61	2013
Learning depth from stereo F Sinz, J Quiñonero-Candela, G Bakır, C Rasmussen, M Franz Pattern Recognition, 245-252, 2004	54	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	49	2003
Scalable clustering A Schwaighofer, JQ Candela, T Borchert, T Graepel, R Herbrich US Patent 8,204,838, 2012	36	2012

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