Tool JEEK: A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
accepted at 2018 ICML
R package: URL
GitRepo for R package: URL
install.packages("jeek")
library(jeek)
demo(jeek)
We consider the problem of including additional knowledge in estimating sparse Gaussian graphical models (sGGMs) from aggregated samples, arising often in bioinformatics and neuroimaging applications. Previous joint sGGM estimators either fail to use existing knowledge or cannot scale-up to many tasks (large
@conference{wang2018jeek,
Author = {Wang, Beilun and Sekhon, Arshdeep and Qi, Yanjun},
Booktitle = {Proceedings of The 35th International Conference on Machine Learning (ICML)},
Title = {A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models},
Year = {2018}}
}
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