Regression

Distribution Matching for Transduction NeurIPS 2009 Dlib-ml: A Machine Learning Toolkit JMLR 2009 Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models NeurIPS 2009 Efficient Learning using Forward-Backward Splitting NeurIPS 2009 Efficient Recovery of Jointly Sparse Vectors NeurIPS 2009 Evolutionary Model Type Selection for Global Surrogate Modeling JMLR 2009 Factor Modeling for Advertisement Targeting NeurIPS 2009 Fast Image Deconvolution using Hyper-Laplacian Priors NeurIPS 2009 Fast, smooth and adaptive regression in metric spaces NeurIPS 2009 Gaussian process regression with Student-t likelihood NeurIPS 2009 Generalization Bounds for Ranking Algorithms via Algorithmic Stability JMLR 2009 Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes NeurIPS 2009 Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction NeurIPS 2009 Heterogeneous multitask learning with joint sparsity constraints NeurIPS 2009 Incorporating Functional Knowledge in Neural Networks JMLR 2009 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Kernels and learning curves for Gaussian process regression on random graphs NeurIPS 2009 Lattice Regression NeurIPS 2009 Learning Non-Linear Combinations of Kernels NeurIPS 2009 Learning to Rank by Optimizing NDCG Measure NeurIPS 2009 Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness NeurIPS 2009 Matrix Completion from Noisy Entries NeurIPS 2009 Matrix Completion from Power-Law Distributed Samples NeurIPS 2009 Maximum likelihood trajectories for continuous-time Markov chains NeurIPS 2009 Nieme: Large-Scale Energy-Based Models JMLR 2009