nips nips2005 nips2005-69 nips2005-69-reference knowledge-graph by maker-knowledge-mining
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Author: Yirong Shen, Matthias Seeger, Andrew Y. Ng
Abstract: The computation required for Gaussian process regression with n training examples is about O(n3 ) during training and O(n) for each prediction. This makes Gaussian process regression too slow for large datasets. In this paper, we present a fast approximation method, based on kd-trees, that significantly reduces both the prediction and the training times of Gaussian process regression.
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