sparse estimation

High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion JMLR 2012 Transelliptical Graphical Models NeurIPS 2012 A blind sparse deconvolution method for neural spike identification NeurIPS 2011 Discussion of “Learning Scale Free Networks by Reweighted ℓ_1 regularization” AISTATS 2011 High-dimensional Covariance Estimation Based On Gaussian Graphical Models JMLR 2011 Learning Scale Free Networks by Reweighted ℓ_1 regularization AISTATS 2011 Sparse Estimation with Structured Dictionaries NeurIPS 2011 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NeurIPS 2011 Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation JMLR 2011 Trace Lasso: a trace norm regularization for correlated designs NeurIPS 2011 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification JMLR 2009 Sparse Estimation Using General Likelihoods and Non-Factorial Priors NeurIPS 2009 Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation NeurIPS 2009 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE NeurIPS 2008 Resolution Limits of Sparse Coding in High Dimensions NeurIPS 2008