Exact Inference for Gaussian Process Regression in Case of Big Data with the Cartesian Product Structure

Download insert_drive_file Link language

Authors:

Belyaev Mikhail, Burnaev Evgeny, Kapushev Yermek

Journal:

ICML 2014 workshop on New Learning Frameworks and Models for Big Data, Beijing 2014

Abstract:

In this paper a new approach for Gaussian Process regression in case of factorial design of experiments is proposed. It allows to efficiently compute exact inference and handle large multidimensional data sets. This functionnality is implemented in MACROS technology.

Keywords: Design of Experiments, Approximation, Gaussian Processes

LinkedIn
VK

Contact Information

location_on  31100, Toulouse, Avenue du Général de Croutte 42

phone  +33 (0) 5 82-95-59-68

mail_outline  info@datadvance.net

Contact us navigate_next