ridge regression

Approximate Steepest Coordinate Descent ICML 2017 Differentially Private Ordinary Least Squares ICML 2017 Encrypted Accelerated Least Squares Regression AISTATS 2017 Faster Principal Component Regression and Stable Matrix Chebyshev Approximation ICML 2017 Generalization Properties of Learning with Random Features NeurIPS 2017 Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging ICML 2017 Subspace Clustering via Variance Regularized Ridge Regression CVPR 2017 Greedy Feature Construction NeurIPS 2016 Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels JMLR 2016 Learning Theory for Distribution Regression JMLR 2016 No penalty no tears: Least squares in high-dimensional linear models ICML 2016 Principal Component Projection Without Principal Component Analysis ICML 2016 Solving Ridge Regression using Sketched Preconditioned SVRG ICML 2016 Staple: Complementary Learners for Real-Time Tracking CVPR 2016 The Teaching Dimension of Linear Learners ICML 2016 The Teaching Dimension of Linear Learners JMLR 2016 Attribute Efficient Linear Regression with Distribution-Dependent Sampling ICML 2015 Two-stage sampled learning theory on distributions AISTATS 2015 Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization ICML 2014 A Residual Bootstrap for High-Dimensional Regression with Near Low-Rank Designs NeurIPS 2014 Efficiency of conformalized ridge regression COLT 2014 Efficient and Accurate Methods for Updating Generalized Linear Models with Multiple Feature Additions JMLR 2014 Elementary Estimators for High-Dimensional Linear Regression ICML 2014 A Risk Comparison of Ordinary Least Squares vs Ridge Regression JMLR 2013 Computation-Risk Tradeoffs for Covariance-Thresholded Regression ICML 2013