Regression

Group Lasso Estimation of High-dimensional Covariance Matrices JMLR 2011 Group Orthogonal Matching Pursuit for Logistic Regression AISTATS 2011 Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation NeurIPS 2011 High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NeurIPS 2011 Information Rates of Nonparametric Gaussian Process Methods JMLR 2011 Kernel Regression in the Presence of Correlated Errors JMLR 2011 k-NN Regression Adapts to Local Intrinsic Dimension NeurIPS 2011 Learning Auto-regressive Models from Sequence and Non-sequence Data NeurIPS 2011 Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors NeurIPS 2011 Learning Transformation Models for Ranking and Survival Analysis JMLR 2011 Multilinear Subspace Regression: An Orthogonal Tensor Decomposition Approach NeurIPS 2011 Multiple Kernel Learning Algorithms JMLR 2011 Non-conjugate Variational Message Passing for Multinomial and Binary Regression NeurIPS 2011 On the accuracy of l1-filtering of signals with block-sparse structure NeurIPS 2011 Optimal aggregation of affine estimators COLT 2011 Optimal learning rates for least squares SVMs using Gaussian kernels NeurIPS 2011 Orthogonal Matching Pursuit with Replacement NeurIPS 2011 Penalty Decomposition Methods for Rank Minimization NeurIPS 2011 Projection onto A Nonnegative Max-Heap NeurIPS 2011 Regression on Fixed-Rank Positive Semidefinite Matrices: A Riemannian Approach JMLR 2011 Robust Gaussian Process Regression with a Student- Likelihood JMLR 2011 Robust Lasso with missing and grossly corrupted observations NeurIPS 2011 RTRMC: A Riemannian trust-region method for low-rank matrix completion NeurIPS 2011 Semi-supervised Regression via Parallel Field Regularization NeurIPS 2011 Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment NeurIPS 2011