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Sparsification for Gaussian Processes for Regression

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If you have a question about this talk, please contact Shakir Mohamed.

In this talk we will give an introduction to Gaussian Processes with the focus on their application to Regression. Since the computational complexity is one of the main problems when dealing with Gaussian Processes, we will give an overview of sparsification methods.

References Rasmussen, C. E. and Williams, C. K. 2005 Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). The MIT Press., 2nd Chapter

Quiñonero-Candela, J. and Rasmussen, C. E. 2005. A Unifying View of Sparse Approximate Gaussian Process Regression. J. Mach. Learn. Res. 6 (Dec. 2005), 1939-1959.

This talk is part of the Machine Learning Reading Group @ CUED series.

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