GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression Academic Article

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. © 2012 Chiwoo Park, Jianhua Z. Huang and Yu Ding.

published proceedings

• JOURNAL OF MACHINE LEARNING RESEARCH

author list (cited authors)

• Park, C., Huang, J. Z., & Ding, Y. u.

complete list of authors

• Park, Chiwoo||Huang, Jianhua Z||Ding, Yu

publication date

• March 2012

publisher

• Journal of Machine Learning Research - JMLR  Publisher

published in

• JOURNAL OF MACHINE LEARNING RESEARCH  Journal

keywords

• Bagging For Gaussian Process
• Domain Decomposition Method
• Gaussian Process Regression
• Local Probabilistic Regression
• Partial Independent Conditional

URI

• https://hdl.handle.net/1969.1/180872

start page

• 775

end page

• 779

volume

• 13