17 citations · 42 across the 5 of their papers we have counts for
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stat.CO2014★ 17 cited
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection
Sang-Yun Oh, Onkar Dalal, Kshitij Khare +1
Sparse high dimensional graphical model selection is a popular topic in contemporary machine learning. To this end, various useful approaches have been proposed in the context of $…
stat.CO2014★ 9 cited
G-AMA: Sparse Gaussian graphical model estimation via alternating minimization
Onkar Dalal, Bala Rajaratnam
Several methods have been recently proposed for estimating sparse Gaussian graphical models using regularization on the inverse covariance matrix. Despite recent advance…
stat.ME2014
Lasso Regression: Estimation and Shrinkage via Limit of Gibbs Sampling
Bala Rajaratnam, Steven Roberts, Doug Sparks +1
The application of the lasso is espoused in high-dimensional settings where only a small number of the regression coefficients are believed to be nonzero. Moreover, statistical pro…