Regression

Heterogeneous-Neighborhood-based Multi-Task Local Learning Algorithms NeurIPS 2013 High-Dimensional Gaussian Process Bandits NeurIPS 2013 High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers AISTATS 2013 How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis JMLR 2013 Human Pose Estimation Using Body Parts Dependent Joint Regressors CVPR 2013 Inverse Density as an Inverse Problem: the Fredholm Equation Approach NeurIPS 2013 It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals NeurIPS 2013 Lasso Screening Rules via Dual Polytope Projection NeurIPS 2013 Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NeurIPS 2013 Learning Heteroscedastic Models by Convex Programming under Group Sparsity ICML 2013 Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression ICML 2013 Learning Stochastic Feedforward Neural Networks NeurIPS 2013 Learning to Estimate and Remove Non-uniform Image Blur CVPR 2013 Least Soft-Threshold Squares Tracking CVPR 2013 Low-Rank Matrix and Tensor Completion via Adaptive Sampling NeurIPS 2013 Matrix Completion From any Given Set of Observations NeurIPS 2013 Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition NeurIPS 2013 Multiscale Dictionary Learning for Estimating Conditional Distributions NeurIPS 2013 Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model ICML 2013 Multivariate Convex Regression with Adaptive Partitioning JMLR 2013 New Subsampling Algorithms for Fast Least Squares Regression NeurIPS 2013 Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery ICML 2013 Nonparametric Sparsity and Regularization JMLR 2013 Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NeurIPS 2013 One-Pass AUC Optimization ICML 2013