Regression

Switched Latent Force Models for Movement Segmentation NeurIPS 2010 The Feature Selection Path in Kernel Methods AISTATS 2010 The Group Dantzig Selector AISTATS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 t-logistic regression NeurIPS 2010 Transduction with Matrix Completion: Three Birds with One Stone NeurIPS 2010 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010 Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach AISTATS 2010 Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels JMLR 2010 Variational Relevance Vector Machine for Tabular Data ACML 2010 A Data-Driven Approach to Modeling Choice NeurIPS 2009 A Gaussian Tree Approximation for Integer Least-Squares NeurIPS 2009 A Least-squares Approach to Direct Importance Estimation JMLR 2009 Asymptotically Optimal Regularization in Smooth Parametric Models NeurIPS 2009 AUC optimization and the two-sample problem NeurIPS 2009 Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity NeurIPS 2009 Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression JMLR 2009 Compressed Least-Squares Regression NeurIPS 2009 Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors JMLR 2009 Convex Relaxation of Mixture Regression with Efficient Algorithms NeurIPS 2009 Data-driven calibration of linear estimators with minimal penalties NeurIPS 2009 Data-driven Calibration of Penalties for Least-Squares Regression JMLR 2009 Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods JMLR 2009 Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning NeurIPS 2009 Directed Regression NeurIPS 2009