Regression

A Comparative Framework for Preconditioned Lasso Algorithms NeurIPS 2013 A Convex Regularizer for Reducing Color Artifact in Color Image Recovery CVPR 2013 Adaptivity to Local Smoothness and Dimension in Kernel Regression NeurIPS 2013 A Framework for Evaluating Approximation Methods for Gaussian Process Regression JMLR 2013 A Generalized Kernel Approach to Structured Output Learning ICML 2013 Aggregating Predictions via Sequential Mini-Trading ACML 2013 A Last-Step Regression Algorithm for Non-Stationary Online Learning AISTATS 2013 A New Convex Relaxation for Tensor Completion NeurIPS 2013 A Risk Comparison of Ordinary Least Squares vs Ridge Regression JMLR 2013 A Unified Robust Regression Model for Lasso-like Algorithms ICML 2013 Bayesian Games for Adversarial Regression Problems ICML 2013 Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC NeurIPS 2013 Bayesian inference for low rank spatiotemporal neural receptive fields NeurIPS 2013 Block Regularized Lasso for Multivariate Multi-Response Linear Regression AISTATS 2013 Class Generative Models Based on Feature Regression for Pose Estimation of Object Categories CVPR 2013 Cluster Analysis: Unsupervised Learning via Supervised Learning with a Non-convex Penalty JMLR 2013 Computationally Efficient Regression on a Dependency Graph for Human Pose Estimation CVPR 2013 Computation-Risk Tradeoffs for Covariance-Thresholded Regression ICML 2013 Consistency of Robust Kernel Density Estimators COLT 2013 Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses NeurIPS 2013 Convex formulations of radius-margin based Support Vector Machines ICML 2013 Convex Relaxations for Permutation Problems NeurIPS 2013 Corrected-Moment Illuminant Estimation ICCV 2013 Correlated random features for fast semi-supervised learning NeurIPS 2013 Crossing the Line: Crowd Counting by Integer Programming with Local Features CVPR 2013