Contact

Dr. Joaquin Quinonero Candela

Raum Nummer: 215

 

Bild von Quinonero Candela, Joaquin, Dr.

Joaquin Quinonero Candela

Position: Wissenschaftler  Abteilung: 

Präferenzen: 
Referenzen pro Seite: Jahr: Medium:

  
Zeige Zusammenfassung

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, (April-2006).
978-3-540-33427-9, Series: Lecture Notes in Computer Science ; 3944

Artikel (2):

Lázaro-Gredilla M, Quiñonero-Candela J, Rasmussen CE und Figueiras-Vidal AR (Juni-2010) Sparse Spectrum Gaussian Process Regression Journal of Machine Learning Research 11 1865-1881.
Quinonero Candela J und Rasmussen CE (Dezember-2005) A Unifying View of Sparse Approximate Gaussian Process Regression Journal of Machine Learning Research 6 1935-1959.

Beiträge zu Tagungsbänden (9):

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, Series: Lecture Notes in Computer Science ; 3944.
pdf
Quinonero Candela J und Rasmussen CE (September-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, Series: Lecture Notes in Computer Science ; 3355.
pdf
Rasmussen CE und Candela JQ (August-2005) Healing the Relevance Vector Machine through Augmentation, 22nd International Conference on Machine Learning (ICML 2005), ACM Press, New York, NY, USA, 689-696.
pdf
Zien A und Candela JQ (August-2005) Large Margin Non-Linear Embedding, 22nd International Conference on Machine Learning (ICML 2005), ACM Press, New York, NY, USA, 1065-1072.
pdf
Sinz F, Candela JQ, BakIr G, Rasmussen CE und Franz M (September-2004) Learning Depth From Stereo In: Pattern Recognition, , 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Springer, Berlin, Germany, 245-252, Series: Lecture Notes in Computer Science ; 3175.
Quinonero Candela J und Winther O (Oktober-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.
pdf
Girard A, Rasmussen CE, Quiñonero-Candela J und Murray-Smith R (Oktober-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.
pdf
Quiñonero-Candela J, Girard A, Larsen J und Rasmussen CE (April-2003) Propagation of Uncertainty in Bayesian Kernel Models: Application to Multiple-Step Ahead Forecasting, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '03), IEEE, Piscataway, NJ, USA, 701-704.
pdf
Quiñonero-Candela J und Hansen LK (2002) Time Series Prediction Based on the Relevance Vector Machine with Adaptive Kernels, 1, 985-988.
default

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).
pdf

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).
pdfps

Poster (1):

Quiñonero-Candela J, Girard A, Larsen J und Rasmussen CE (September-2003): Propagation of Uncertainty in Bayesian Kernel Models: Application to Multiple-Step Ahead Forecasting, 13th IEEE International Workshop on Neural Networks for Signal Processing (NNSP '03), Toulouse, France.

Abschlussarbeiten (1):

Quiñonero-Candela J: Learning with Uncertainty - Gaussian Processes and Relevance Vector Machines, Technical University of Denmark, Lyngby, Denmark, (Mai-2004). PhD thesis
pdf

Export als:
BibTeX, XML, pubman, Edoc, RTF
Last updated: Montag, 22.05.2017