Some Approximation Bounds For Sparse Gaussian Processes

Gaussian processes have been widely applied to regression problems with good performance.
However, they can be computationally expensive. Recently, there have been studies on using sparse approximations in Gaussian processes in order to reduce the computational cost. In this paper, we investigate properties of certain sparse algorithms that approximately solve a Gaussian process.
We obtain approximation bounds, and compare our results with related methods.

By: Tong Zhang

Published in: RC22010 in 2001

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