l1 regularization

Fast Active-set-type Algorithms for l1-regularized Linear Regression AISTATS 2010 Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity AISTATS 2010 Learning Multiple Tasks with a Sparse Matrix-Normal Penalty NeurIPS 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Linear Complementarity for Regularized Policy Evaluation and Improvement NeurIPS 2010 Multi-Stage Dantzig Selector NeurIPS 2010 The Feature Selection Path in Kernel Methods AISTATS 2010 L_1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry NeurIPS 2009 Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NeurIPS 2009 Efficient Learning using Forward-Backward Splitting NeurIPS 2009 Sparse and Locally Constant Gaussian Graphical Models NeurIPS 2009 Sparse Online Learning via Truncated Gradient JMLR 2009 An Homotopy Algorithm for the Lasso with Online Observations NeurIPS 2008 An interior-point stochastic approximation method and an L1-regularized delta rule NeurIPS 2008 Multi-stage Convex Relaxation for Learning with Sparse Regularization NeurIPS 2008 Sparse Online Learning via Truncated Gradient NeurIPS 2008 A New View of Automatic Relevance Determination NeurIPS 2007 An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression JMLR 2007 Blind channel identification for speech dereverberation using l1-norm sparse learning NeurIPS 2007 Compressed Regression NeurIPS 2007 Discriminative Log-Linear Grammars with Latent Variables NeurIPS 2007 Efficient sparse coding algorithms NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 High-Dimensional Graphical Model Selection Using ℓ_1-Regularized Logistic Regression NeurIPS 2006 Dimensionality Reduction via Sparse Support Vector Machines JMLR 2003