Sparse Optimization

EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NeurIPS 2011 Generalized Lasso based Approximation of Sparse Coding for Visual Recognition NeurIPS 2011 Greedy Algorithms for Structurally Constrained High Dimensional Problems NeurIPS 2011 Large-Scale Sparse Principal Component Analysis with Application to Text Data NeurIPS 2011 Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NeurIPS 2011 Minimax Localization of Structural Information in Large Noisy Matrices NeurIPS 2011 Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels NeurIPS 2011 On Learning Discrete Graphical Models using Greedy Methods NeurIPS 2011 Robust Lasso with missing and grossly corrupted observations NeurIPS 2011 Shaping Level Sets with Submodular Functions NeurIPS 2011 Sparse Features for PCA-Like Linear Regression NeurIPS 2011 Sparse recovery by thresholded non-negative least squares NeurIPS 2011 Statistical Tests for Optimization Efficiency NeurIPS 2011 Trace Lasso: a trace norm regularization for correlated designs NeurIPS 2011 Accounting for network effects in neuronal responses using L1 regularized point process models NeurIPS 2010 Adaptive Multi-Task Lasso: with Application to eQTL Detection NeurIPS 2010 A Dirty Model for Multi-task Learning NeurIPS 2010 A Family of Penalty Functions for Structured Sparsity NeurIPS 2010 A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups NeurIPS 2010 CUR from a Sparse Optimization Viewpoint NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection 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