sparse estimation

On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior AISTATS 2017 SVD-Based Screening for the Graphical Lasso IJCAI 2017 Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016 A Well-Conditioned and Sparse Estimation of Covariance and Inverse Covariance Matrices Using a Joint Penalty JMLR 2016 Generalized Direct Change Estimation in Ising Model Structure ICML 2016 Maximal Sparsity with Deep Networks? NeurIPS 2016 The Multiple Quantile Graphical Model NeurIPS 2016 Trend Filtering on Graphs JMLR 2016 High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality NeurIPS 2015 Non-convex Statistical Optimization for Sparse Tensor Graphical Model NeurIPS 2015 Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso NeurIPS 2015 Swept Approximate Message Passing for Sparse Estimation ICML 2015 The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R JMLR 2015 The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models AISTATS 2015 Vector-Space Markov Random Fields via Exponential Families ICML 2015 Gaussian Copula Precision Estimation with Missing Values AISTATS 2014 Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection NeurIPS 2014 The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R JMLR 2014 Better Approximation and Faster Algorithm Using the Proximal Average NeurIPS 2013 Dirty Statistical Models NeurIPS 2013 Large Scale Distributed Sparse Precision Estimation NeurIPS 2013 Learning Heteroscedastic Models by Convex Programming under Group Sparsity ICML 2013 Sparse Inverse Covariance Estimation with Calibration NeurIPS 2013 Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory JMLR 2013 Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization NeurIPS 2013