Feature Selection

Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness AISTATS 2012 Forward Basis Selection for Sparse Approximation over Dictionary AISTATS 2012 Fused sparsity and robust estimation for linear models with unknown variance NeurIPS 2012 Gradient-based kernel method for feature extraction and variable selection NeurIPS 2012 Graphical Models via Generalized Linear Models NeurIPS 2012 High-Dimensional Structured Feature Screening Using Binary Markov Random Fields AISTATS 2012 High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction NeurIPS 2012 Imitation Learning by Coaching NeurIPS 2012 Informative Priors for Markov Blanket Discovery AISTATS 2012 Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization AISTATS 2012 Local Kernel Density Ratio-Based Feature Selection for Outlier Detection ACML 2012 Local Supervised Learning through Space Partitioning NeurIPS 2012 Projection Retrieval for Classification NeurIPS 2012 Selecting Diverse Features via Spectral Regularization NeurIPS 2012 Sparse Higher-Order Principal Components Analysis AISTATS 2012 Sparsistency of the Edge Lasso over Graphs AISTATS 2012 Structured Sparse Canonical Correlation 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 EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NeurIPS 2011 Group Lasso Estimation of High-dimensional Covariance Matrices JMLR 2011 Group Orthogonal Matching Pursuit for Logistic Regression AISTATS 2011 Hashing Algorithms for Large-Scale Learning NeurIPS 2011