no code implementations • NeurIPS 2013 • Cho-Jui Hsieh, Matyas A. Sustik, Inderjit S. Dhillon, Pradeep K. Ravikumar, Russell Poldrack
The l1-regularized Gaussian maximum likelihood estimator (MLE) has been shown to have strong statistical guarantees in recovering a sparse inverse covariance matrix even under high-dimensional settings.
no code implementations • NeurIPS 2011 • Cho-Jui Hsieh, Matyas A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
The L1-regularized Gaussian maximum likelihood estimator (MLE) has been shown to have strong statistical guarantees in recovering a sparse inverse covariance matrix, or alternatively the underlying graph structure of a Gaussian Markov Random Field, from very limited samples.