sparse regression

Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012 Private Convex Empirical Risk Minimization and High-dimensional Regression COLT 2012 Robust Multi-task Regression with Grossly Corrupted Observations AISTATS 2012 Sparse Prediction with the k-Support Norm NeurIPS 2012 Sparsistency of the Edge Lasso over Graphs AISTATS 2012 Greedy Algorithms for Structurally Constrained High Dimensional Problems NeurIPS 2011 Sparse Estimation with Structured Dictionaries NeurIPS 2011 A Family of Penalty Functions for Structured Sparsity NeurIPS 2010 CUR from a Sparse Optimization Viewpoint NeurIPS 2010 Descent Methods for Tuning Parameter Refinement AISTATS 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 Fast global convergence rates of gradient methods for high-dimensional statistical recovery NeurIPS 2010 Multi-Stage Dantzig Selector NeurIPS 2010 Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression NeurIPS 2010 Restricted Eigenvalue Properties for Correlated Gaussian Designs JMLR 2010 Sparse Instrumental Variables (SPIV) for Genome-Wide Studies NeurIPS 2010 The Group Dantzig Selector AISTATS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach AISTATS 2010 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NeurIPS 2009 Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction NeurIPS 2009 On the Consistency of Feature Selection using Greedy Least Squares Regression JMLR 2009 Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation NeurIPS 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009