Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation

Kian Hsiang Low, Jiangbo Yu, Jie Chen +1

The expressive power of a Gaussian process (GP) model comes at a cost of poor scalability in the data size. To improve its scalability, this paper presents a low-rank-cum-Markov ap…