GPLP: a local and parallel computation toolbox for Gaussian process regression

Authors:
Chiwoo Park;Jianhua Z. Huang;Yu Ding
Affiliations:
Department of Industrial and Manufacturing Engineering, Florida A&M - Florida State University College of Engineering, Tallahassee, FL;Department of Statistics, Texas A&M University, College Station, TX;Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX
Venue:
The Journal of Machine Learning Research
Year:
2012

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Abstract

This paper presents the Getting-started style documentation for the local and parallel computation toolbox for Gaussian process regression (GPLP), an open source software package written in Matlab (but also compatible with Octave). The working environment and the usage of the software package will be presented in this paper.