Honglei Guo, Jianmin Jiang, et al.
IJCNLP 2004
Gaussian processes have been widely applied to regression problems with good performance. However, they can be computationally expensive. In order to reduce the computational cost, there have been recent studies on using sparse approximations in gaussian processes. In this article, we investigate properties of certain sparse regression algorithms that approximately solve a gaussian process. We obtain approximation bounds and compare our results with related methods.
Honglei Guo, Jianmin Jiang, et al.
IJCNLP 2004
Tong Zhang
Machine Learning
Rie Kubota Ando, Tong Zhang
NeurIPS 2006
Ron Meir, Tong Zhang
NeurIPS 2002