Sparse Optimization

Exclusive Feature Learning on Arbitrary Structures via ℓ_1,2-norm NeurIPS 2014 Finding a sparse vector in a subspace: Linear sparsity using alternating directions NeurIPS 2014 Generalized Dantzig Selector: Application to the k-support norm NeurIPS 2014 On Sparse Gaussian Chain Graph Models NeurIPS 2014 Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection NeurIPS 2014 Parallel Feature Selection Inspired by Group Testing NeurIPS 2014 Preconditioning for Accelerated Iteratively Reweighted Least Squares in Structured Sparsity Reconstruction CVPR 2014 Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators NeurIPS 2014 Sparse PCA via Covariance Thresholding NeurIPS 2014 Sparse PCA with Oracle Property NeurIPS 2014 Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space NeurIPS 2014 Tight convex relaxations for sparse matrix factorization NeurIPS 2014 Total-Variation Minimization on Unstructured Volumetric Mesh: Biophysical Applications on Reconstruction of 3D Ischemic Myocardium CVPR 2014 Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets NeurIPS 2014 Zeta Hull Pursuits: Learning Nonconvex Data Hulls NeurIPS 2014 A Comparative Framework for Preconditioned Lasso Algorithms NeurIPS 2013 Bellman Error Based Feature Generation using Random Projections on Sparse Spaces NeurIPS 2013 BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables NeurIPS 2013 Block Regularized Lasso for Multivariate Multi-Response Linear Regression AISTATS 2013 Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models NeurIPS 2013 Convex Tensor Decomposition via Structured Schatten Norm Regularization NeurIPS 2013 Dirty Statistical Models NeurIPS 2013 Estimating LASSO Risk and Noise Level NeurIPS 2013 Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA NeurIPS 2013 Image Tag Completion via Image-Specific and Tag-Specific Linear Sparse Reconstructions CVPR 2013