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Proceedings (1): | |
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Quinonero Candela J  , , and : 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  
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Articles (2): | |
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, Quiñonero-Candela J , Rasmussen CE and (2010) Sparse Spectrum Gaussian Process Regression
Journal of Machine Learning Research 11 1865-1881.
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Quinonero Candela J and Rasmussen CE (2005) A Unifying View of Sparse Approximate Gaussian Process Regression
Journal of Machine Learning Research 6 1935-1959.
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Conference papers (10): | |
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Quinonero Candela J , Rasmussen CE , Sinz F , Bousquet O and Schölkopf B (2006) Evaluating Predictive Uncertainty Challenge
In: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment, (Ed) , , and , First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Springer, Berlin, Germany, 1-27.
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Zien A and Candela JQ (2005) Large Margin Non-Linear Embedding
In: ICML 2005, (Ed) De Raedt, L. , S. Wrobel, 22nd International Conference on Machine Learning, ACM Press, New York, NY, USA, 1065-1072.
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Quinonero Candela J and Rasmussen CE (2005) Analysis of Some Methods for Reduced Rank Gaussian Process Regression
In: Switching and Learning in Feedback Systems, (Ed) Murray Smith, R. , R. Shorten, European Summer School on Multi-Agent Control 2003, Springer, Berlin, Germany, 98-127.
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Rasmussen CE and Candela JQ (2005) Healing the Relevance Vector Machine through Augmentation
(Ed) De Raedt, L. , S. Wrobel, ICML 2005, 689.
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Sinz F , Candela JQ , BakIr G , Rasmussen CE and Franz M (2004) Learning Depth From Stereo
In: 26th DAGM Symposium, (Ed) Rasmussen, C. E., H. H. Bülthoff, B. Schölkopf, M. A. Giese, 26th DAGM Symposium, Springer, Berlin, Germany, 245-252.
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Quinonero Candela J and (2003) Incremental Gaussian Processes
In: Advances in Neural Information Processing Systems 15, (Ed) Becker, S. , S. Thrun, K. Obermayer, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 1001-1008.
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, Rasmussen CE , Quiñonero-Candela J and (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, (Ed) Becker, S. , S. Thrun, K. Obermayer, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 529-536.
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Quiñonero-Candela J , , and Rasmussen CE (2003) Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting
(Ed) and , Proceedings of 2003 IEEE International Workshop on Neural Networks for Signal Processing, 0-0.
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Quiñonero-Candela J , , and 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.
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Quiñonero-Candela J and (2002) Time Series Prediction Based on the Relevance Vector Machine with Adaptive Kernels
, 1, 985-988.
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Contributions to books (1): | |
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Quiñonero-Candela J , Rasmussen CE and : Approximation Methods for Gaussian Process Regression, 203-223.
In: Large-Scale Kernel Machines, (Ed) Bottou, L. , O. Chapelle, D. DeCoste, J. Weston, MIT Press, Cambridge, MA, USA, (2007).
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Technical reports (1): | |
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Quiñonero-Candela J , and 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).
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Theses (1): | |
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Quiñonero-Candela J : Learning with Uncertainty - Gaussian Processes and Relevance Vector Machines, Technical University of Denmark, Lyngby, Denmark, (2004).
PhD thesis
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