Variable selection using Gaussian process regression-based metrics for high-dimensional model approximation with limited data

2018 ◽  
Vol 59 (5) ◽  
pp. 1439-1454 ◽  
Author(s):  
Kyungeun Lee ◽  
Hyunkyoo Cho ◽  
Ikjin Lee
Keyword(s):  
Variable Selection ◽  
Gaussian Process ◽  
Gaussian Process Regression ◽  
High Dimensional ◽  
Limited Data ◽  
Dimensional Model ◽  
Model Approximation

scholarly journals High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

2017 ◽  
Vol 50 (1) ◽  
pp. 77-96 ◽  
Author(s):  
Charanraj A. Thimmisetty ◽  
Roger G. Ghanem ◽  
Joshua A. White ◽  
Xiao Chen
Keyword(s):  
Gaussian Process ◽  
Gaussian Process Regression ◽  
High Dimensional ◽  
Diffusion Maps ◽  
And Diffusion

scholarly journals Pairwise Variable Selection for High-Dimensional Model-Based Clustering

Biometrics ◽  
2009 ◽  
Vol 66 (3) ◽  
pp. 793-804 ◽  
Author(s):  
Jian Guo ◽  
Elizaveta Levina ◽  
George Michailidis ◽  
Ji Zhu
Keyword(s):  
Variable Selection ◽  
High Dimensional ◽  
Dimensional Model ◽  
Model Based Clustering ◽  
Model Based ◽  
Selection For
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