Filtered Gaussian Processes for Learning with Large Data-Sets
Shi, Jian Qing and Murray-Smith, Roderick and Titterington, D. Mike and Pearlmutter, Barak A. (2005) Filtered Gaussian Processes for Learning with Large Data-Sets. Lecture Notes in Computer Science (3355). pp. 128-139. ISSN 0302-9743
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those methods to problems with large data-sets. In this paper we develop a filtering approach based on a Gaussian process regression model. The idea is to generate a smalldimensional set of filtered data that keeps a high proportion of the information contained in the original large data-set. Model learning and prediction are based on the filtered data, thereby decreasing the computational burden dramatically.
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