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Dr. Joaquin Quinonero Candela

Raum Nummer:	215
E-Mail:	jqc

Bild von Quinonero Candela, Joaquin, Dr.

Joaquin Quinonero Candela

Position: Wissenschaftler Abteilung: Alumni Schölkopf

Publikationen

Tagungsbände (1):
•	Quinonero Candela J , Dagan I , Magnini B und Lauria F : Machine Learning Challenges: evaluating predictive uncertainty, visual object classification and recognising textual entailment, First Pascal Machine Learning Challenges Workshop (MLCW 2005), 462, Springer, Heidelberg, Germany, (2006). 978-3-540-33427-9
Artikel (2):
•	Lázaro-Gredilla M , Quiñonero-Candela J , Rasmussen CE und Figueiras-Vidal AR (June-2010) Sparse Spectrum Gaussian Process Regression Journal of Machine Learning Research 11 1865-1881.
•	Quinonero Candela J und Rasmussen CE (December-2005) A Unifying View of Sparse Approximate Gaussian Process Regression Journal of Machine Learning Research 6 1935-1959.
Beiträge zu Tagungsbänden (10):
•	Quinonero Candela J , Rasmussen CE , Sinz F , Bousquet O und Schölkopf B (April-2006) Evaluating Predictive Uncertainty Challenge In: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment, First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Springer, Berlin, Germany, 1-27.
•	Zien A und Candela JQ (August-2005) Large Margin Non-Linear Embedding In: ICML 2005, 22nd International Conference on Machine Learning, ACM Press, New York, NY, USA, 1065-1072.
•	Quinonero Candela J und Rasmussen CE (2005) Analysis of Some Methods for Reduced Rank Gaussian Process Regression In: Switching and Learning in Feedback Systems, European Summer School on Multi-Agent Control 2003, Springer, Berlin, Germany, 98-127.
•	Rasmussen CE und Candela JQ (2005) Healing the Relevance Vector Machine through Augmentation ICML 2005, 689.
•	Sinz F , Candela JQ , BakIr G , Rasmussen CE und Franz M (September-2004) Learning Depth From Stereo In: 26th DAGM Symposium, 26th DAGM Symposium, Springer, Berlin, Germany, 245-252.
•	Quinonero Candela J und Winther O (October-2003) Incremental Gaussian Processes In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 1001-1008.
•	Girard A , Rasmussen CE , Quiñonero-Candela J und Murray-Smith R (October-2003) Multiple-step ahead prediction for non linear dynamic systems: A Gaussian Process treatment with propagation of the uncertainty In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 529-536.
•	Quiñonero-Candela J , Girard A , Larsen J und Rasmussen CE (2003) Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting Proceedings of 2003 IEEE International Workshop on Neural Networks for Signal Processing, 0-0.
•	Quiñonero-Candela J , Girard A , Larsen J und Rasmussen CE (2003) Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting IEEE International Conference on Acoustics, Speech and Signal Processing, 2, 701-704.
•	Quiñonero-Candela J und Hansen LK (2002) Time Series Prediction Based on the Relevance Vector Machine with Adaptive Kernels , 1, 985-988.
Beiträge zu Büchern (1):
•	Quiñonero-Candela J , Rasmussen CE und Williams CKI : Approximation Methods for Gaussian Process Regression, 203-223. In: Large-Scale Kernel Machines, (Ed) L. Bottou, MIT Press, Cambridge, MA, USA, (September-2007).
Technische Berichte (1):
•	Quiñonero-Candela J , Girard A und Rasmussen CE : Prediction at an Uncertain Input for Gaussian Processes and Relevance Vector Machines - Application to Multiple-Step Ahead Time-Series Forecasting, IMM-2003-18, (2003).
Abschlussarbeiten (1):
•	Quiñonero-Candela J : Learning with Uncertainty - Gaussian Processes and Relevance Vector Machines, Technical University of Denmark, Lyngby, Denmark, (May-2004). PhD thesis