I am a Senior Applied Researcher at Microsoft adCenter and I lead a team embedded in Microsoft Research Cambridge, part of the Online Services and Advertising team. Our work is focussed on the application of large scale machine learning and probabilistic modelling techniques to modelling and predicting online user behaviour, and to games. Yes... games! I have led a team that has created a game that will soon be released on the Xbox 360. :-) Stay tuned!
Before joining Microsoft Research Cambridge, I was a postdoctoral researcher at the Fraunhofer Institute in Berlin and at the Technical University of Berlin with Prof. Klaus-Robert Müller. Before that, I was a postdoctoral researcher at the Max Planck Institute for Biological Cybernetics in the beautiful town of Tübingen in Southern Germany, working with my PhD advisor Dr. Carl E. Rasmussen and with Prof. Bernhard Schölkopf
I received my PhD from the Technical University of Denmark, where I worked with Lars Kai Hansen, Jan Larsen and Ole Winter in the Intelligent Signal Processing group. Prior to that, I graduated as a Telecommunications Engineer at the Carlos III University of Madrid, where I worked with Prof. Anibal Figueiras-Vidal, who first introduced me to machine learning.
Miguel Lázaro-Gredilla, Joaquin Quiñonero Candela, Carl Edward Rasmussen, and Aníbal R. Figueiras-Vidal, Sparse Spectrum Gaussian Process Regression, in Journal of Machine Learning Research, vol. 11, pp. 1865-1881, 15 June 2010
Thore Graepel, Joaquin Quinonero Candela, Thomas Borchert, and Ralf Herbrich, Web-Scale Bayesian Click-Through Rate Prediction for Sponsored Search Advertising in Microsoft’s Bing Search Engine, in Proceedings of the 27th International Conference on Machine Learning ICML 2010, Invited Applications Track (unreviewed, to appear), June 2010
J. Quiñonero Candela, M. Sugiyama, A. Schwaighofer, and N. D. Lawrence, Dataset Shift in Machine Learning, MIT Press, 2009
Anton Schwaighofer, Joaquin Quinonero Candela, Thomas Borchert, Thore Graepel, and Ralf Herbrich, Scalable Clustering and Keyword Suggestion for Online Advertisements, in Proceedings of ADKDD 2009: 3rd Annual International Workshop on Data Mining and Audience Intelligence for Advertising, Association for Computing Machinery, Inc., 2009
Miguel Lazaro-Gredilla, Joaquin Quiñonero Candela, and Anibal Figueiras-Vidal, Sparse Spectral Sampling Gaussian Processes, no. MSR-TR-2007-152, November 2007
Joaquin Quiñonero Candela, Edward Snelson, and Oliver Williams, Sensible Priors for Sparse Bayesian Learning, no. MSR-TR-2007-121, September 2007
Joaquin Quiñonero Candela, Carl Edward Rasmussen, and Christopher K. I. Williams, Approximation Methods for Gaussian Process Regression, no. MSR-TR-2007-124, September 2007
J. Quiñonero Candela, C. E. Rasmussen, and C. K. I. Williams, Approximation Methods for Gaussian Process Regression, in Large Scale Learning Machines, pp. 203–223, MIT Press, 2007
Neil D. Lawrence, Anton Schwaighofer, and Joaquin Quiñonero Candela, Gaussian Processes in Practice, 2007
N. D. Lawrence and J. Quiñonero Candela, Local Distance Preservation in the GP-LVM Through Back Constraints, in Proceedings of the 23rd International Conference on Machine Learning, 2006
J. Quiñonero Candela, I. Dagan, B. Magnini, and F. D'Alché, Machine Learning Challenges - Evaluating Predictive Uncertainty, Textual Entailment and Object Recognition Systems, vol. 3944, Springer Verlag, 2006
J. Quiñonero Candela and C. E. Rasmussen, A Unifying View of Sparse Approximate Gaussian Process Regression, in Journal of Machine Learning Research, pp. 1935–1959, 2006
J. Quiñonero Candela, C. E. Rasmussen, F. Sinz, O. Bousquet, and B. Schölkopf, Evaluating Predictive Uncertainty Challenge, in Machine Learning Challenges - Evaluating Predictive Uncertainty, Textual Entailment and Object Recognition Systems, vol. 3944, pp. 1–27, Springer, 2006
A. Zien and J. Quiñonero Candela, Large Margin Non-linear Embedding, in Proceedings of the 22nd International Conference on Machine Learning, 2005
J. Quiñonero Candela and C. E. Rasmussen, Analysis of some methods for reduced rank Gaussian process regression, in Switching and Learning in Feedback Systems, vol. 3355, pp. 98-127, Springer Verlag, 2005
C. E. Rasmussen and J. Quiñonero Candela, Healing the Relevance Vector Machine through Augmentation, in Proceedings of the 22nd International Conference on Machine Learning, 2005
F. Sinz, J. Quiñonero Candela, G. H. Bakir, C. E. Rasmussen, and M. O. Franz, Learning Depth from Stereo, in Proceedings of the 26th DAGM Symposium, 2004
J. Quiñonero Candela, Learning with Uncertainty - Gaussian Processes and Relevance Vector Machines, 2004
J. Quiñonero Candela, A. Girard, J. Larsen, and C. E. Rasmussen, Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting, in Proceedings of the International Conference on Acoustics, Speech and Signal Processing Conference, 2003
A. Girard, C. E. Rasmussen, J. Quiñonero Candela, and R. Murray-Smith, Gaussian Process Priors with Uncertain Inputs - Application to Multiple-Step Ahead Time Series Forecasting, in Advances in Neural Information Processing Systems 15, 2003
J. Quiñonero Candela and O. Winther, Incremental Gaussian Processes, in Advances in Neural Information Processing Systems 15, 2003
J. Quiñonero Candela and L. K. Hansen, Time Series Prediction Based on the Relevance Vector Machine with Adaptive Kernels, in Proceedings of the International Conference on Acoustics, Speech and Signal Processing Conference, 2002
- The Path of Go was released for the Xbox 360 on December 15th 2010.
- I gave a talk at the NIPS 2010 Machine Learning in Online Advertising Workshop
- Title: "AdPredictor – Large Scale Bayesian Click-Through Rate Prediction in Microsoft’s Bing Search Engine".
- Remember: Microsoft adCenter now delivers all ads on Bing and on Yahoo!, and Bing also powers all search results on Yahoo! :-)
- A nice article about our work on click prediction for Bing and Yahoo! in the MIT Technology Review.
- The book Dataset Shift in Machine Learning which I had the pleasure of coediting with Masashi Sugiyama, Anton Schwaighofer and Neil Lawrence went to press a while ago now.
- I not-so-recently co-organized the workshop Beyond Search: Computational Intelligence for the Web at the 2008 Advances in Neural Information Processing Systems (NIPS*08) Conference.
