5 results
(BibTeX)

**Evaluating Predictive Uncertainty Challenge**
In *Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment*, pages: 1-27, (Editors: J Quiñonero Candela and I Dagan and B Magnini and F d’Alché-Buc), Springer, Berlin, Germany, First PASCAL Machine Learning Challenges Workshop (MLCW), April 2006 (inproceedings)

**Machine Learning Challenges: evaluating predictive uncertainty, visual object classification and recognising textual entailment**
*Proceedings of the First Pascal Machine Learning Challenges Workshop on Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment (MLCW 2005)*, pages: 462, Lecture Notes in Computer Science, Springer, Heidelberg, Germany, First Pascal Machine Learning Challenges Workshop (MLCW), 2006 (proceedings)

**Analysis of Some Methods for Reduced Rank Gaussian Process Regression**
In *Switching and Learning in Feedback Systems*, pages: 98-127, (Editors: Murray Smith, R. , R. Shorten), Springer, Berlin, Germany, European Summer School on Multi-Agent Control, 2005 (inproceedings)

**A Unifying View of Sparse Approximate Gaussian Process Regression**
*Journal of Machine Learning Research*, 6, pages: 1935-1959, December 2005 (article)

**Incremental Gaussian Processes**
In *Advances in Neural Information Processing Systems 15*, pages: 1001-1008, (Editors: Becker, S. , S. Thrun, K. Obermayer), MIT Press, Cambridge, MA, USA, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)