Regression

Multi-task Gaussian Process Learning of Robot Inverse Dynamics NeurIPS 2008 Non-Parametric Modeling of Partially Ranked Data JMLR 2008 Nonparametric regression and classification with joint sparsity constraints NeurIPS 2008 Non-parametric Regression Between Manifolds NeurIPS 2008 On the Suitable Domain for SVM Training in Image Coding JMLR 2008 Optimal Response Initiation: Why Recent Experience Matters NeurIPS 2008 Overlaying classifiers: a practical approach for optimal ranking NeurIPS 2008 Phase transitions for high-dimensional joint support recovery NeurIPS 2008 Predicting the Geometry of Metal Binding Sites from Protein Sequence NeurIPS 2008 Privacy-preserving logistic regression NeurIPS 2008 Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking NeurIPS 2008 Robust Regression and Lasso NeurIPS 2008 Simple Local Models for Complex Dynamical Systems NeurIPS 2008 Sparse Convolved Gaussian Processes for Multi-output Regression NeurIPS 2008 Sparse Online Learning via Truncated Gradient NeurIPS 2008 Sparsity of SVMs that use the epsilon-insensitive loss NeurIPS 2008 Structured ranking learning using cumulative distribution networks NeurIPS 2008 Tighter Bounds for Structured Estimation NeurIPS 2008 Value Function Approximation using Multiple Aggregation for Multiattribute Resource Management JMLR 2008 A Bayesian Framework for Cross-Situational Word-Learning NeurIPS 2007 A Constraint Generation Approach to Learning Stable Linear Dynamical Systems NeurIPS 2007 Active Preference Learning with Discrete Choice Data NeurIPS 2007 Adaptive Non-Stationary Kernel Regression for Terrain Modeling RSS 2007 A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning JMLR 2007 A Spectral Regularization Framework for Multi-Task Structure Learning NeurIPS 2007