feature selection

Sparse Higher-Order Principal Components Analysis AISTATS 2012 Transelliptical Component Analysis NeurIPS 2012 Universal Measurement Bounds for Structured Sparse Signal Recovery AISTATS 2012 Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity NeurIPS 2012 Efficient Methods for Overlapping Group Lasso NeurIPS 2011 Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis NeurIPS 2011 Large-Scale Category Structure Aware Image Categorization NeurIPS 2011 Large-Scale Sparse Principal Component Analysis with Application to Text Data NeurIPS 2011 Learning a Tree of Metrics with Disjoint Visual Features NeurIPS 2011 Learning Higher-Order Graph Structure with Features by Structure Penalty NeurIPS 2011 Learning with Structured Sparsity JMLR 2011 Online Learning of Structured Predictors with Multiple Kernels AISTATS 2011 Prismatic Algorithm for Discrete D.C. Programming Problem NeurIPS 2011 Projection onto A Nonnegative Max-Heap NeurIPS 2011 Stochastic Methods for -regularized Loss Minimization JMLR 2011 Trace Lasso: a trace norm regularization for correlated designs NeurIPS 2011 Understanding the Intrinsic Memorability of Images NeurIPS 2011 Union Support Recovery in Multi-task Learning JMLR 2011 A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification JMLR 2010 A Fast Hybrid Algorithm for Large-Scale -Regularized Logistic Regression JMLR 2010 Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization NeurIPS 2010 Fast Active-set-type Algorithms for l1-regularized Linear Regression AISTATS 2010 Feature Selection using Multiple Streams AISTATS 2010 Linear Complementarity for Regularized Policy Evaluation and Improvement NeurIPS 2010 Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation JMLR 2010