Sparse Optimization

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NeurIPS 2011 Sparse Manifold Clustering and Embedding NeurIPS 2011 Sparse recovery by thresholded non-negative least squares NeurIPS 2011 Sparse Recovery with Brownian Sensing NeurIPS 2011 Trace Lasso: a trace norm regularization for correlated designs NeurIPS 2011 Universal low-rank matrix recovery from Pauli measurements NeurIPS 2011 Accounting for network effects in neuronal responses using L1 regularized point process models NeurIPS 2010 A Dirty Model for Multi-task Learning NeurIPS 2010 A Family of Penalty Functions for Structured Sparsity NeurIPS 2010 An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA NeurIPS 2010 A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups NeurIPS 2010 CUR from a Sparse Optimization Viewpoint NeurIPS 2010 Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization NeurIPS 2010 Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010 Fast detection of multiple change-points shared by many signals using group LARS NeurIPS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection NeurIPS 2010 Learning Multiple Tasks with a Sparse Matrix-Normal Penalty NeurIPS 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Moreau-Yosida Regularization for Grouped Tree Structure Learning NeurIPS 2010 Multi-Stage Dantzig Selector NeurIPS 2010 Multivariate Dyadic Regression Trees for Sparse Learning Problems NeurIPS 2010 Network Flow Algorithms for Structured Sparsity NeurIPS 2010 Structured sparsity-inducing norms through submodular functions NeurIPS 2010 Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework NeurIPS 2010