Regression

Accelerated Training for Matrix-norm Regularization: A Boosting Approach NeurIPS 2012 A Comparison of the Lasso and Marginal Regression JMLR 2012 Active Learning of Multi-Index Function Models NeurIPS 2012 Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting NeurIPS 2012 A General Framework for Structured Sparsity via Proximal Optimization AISTATS 2012 A Geometric take on Metric Learning NeurIPS 2012 Algorithms for Learning Kernels Based on Centered Alignment JMLR 2012 A Marginalized Particle Gaussian Process Regression NeurIPS 2012 A Multi-Stage Framework for Dantzig Selector and LASSO JMLR 2012 A Polynomial-time Form of Robust Regression NeurIPS 2012 A Two-Graph Guided Multi-task Lasso Approach for eQTL Mapping AISTATS 2012 Bayesian Warped Gaussian Processes NeurIPS 2012 Calibrated Elastic Regularization in Matrix Completion NeurIPS 2012 Collaborative Gaussian Processes for Preference Learning NeurIPS 2012 Consistent Model Selection Criteria on High Dimensions JMLR 2012 Dual-Space Analysis of the Sparse Linear Model NeurIPS 2012 Efficient and direct estimation of a neural subunit model for sensory coding NeurIPS 2012 Ensemble weighted kernel estimators for multivariate entropy estimation NeurIPS 2012 Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications JMLR 2012 Expectation Propagation in Gaussian Process Dynamical Systems NeurIPS 2012 Fused sparsity and robust estimation for linear models with unknown variance NeurIPS 2012 Generic Methods for Optimization-Based Modeling AISTATS 2012 glm-ie: Generalised Linear Models Inference & Estimation Toolbox JMLR 2012 GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression JMLR 2012 Gradient Weights help Nonparametric Regressors NeurIPS 2012