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Regression

4964 directly classified papers

Papers per year

Papers

A New Algorithm for Estimating the Effective Dimension-Reduction Subspace JMLR 2008
A Tutorial on Conformal Prediction JMLR 2008
Bayesian Inference and Optimal Design for the Sparse Linear Model JMLR 2008
Bouligand Derivatives and Robustness of Support Vector Machines for Regression JMLR 2008
Consistency of the Group Lasso and Multiple Kernel Learning JMLR 2008
Predicting Partial Paths from Planning Problem Parameters RSS 2007
Adaptive Non-Stationary Kernel Regression for Terrain Modeling RSS 2007
Hierarchical Penalization NIPS 2007
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems NIPS 2007
How SVMs can estimate quantiles and the median NIPS 2007
Non-parametric Modeling of Partially Ranked Data NIPS 2007
Characterizing the Function Space for Bayesian Kernel Models JMLR 2007
Feature Selection Methods for Improving Protein Structure Prediction with Rosetta NIPS 2007
A Bayesian Framework for Cross-Situational Word-Learning NIPS 2007
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NIPS 2007
Bundle Methods for Machine Learning NIPS 2007
On Ranking in Survival Analysis: Bounds on the Concordance Index NIPS 2007
Robust Regression with Twinned Gaussian Processes NIPS 2007
Better than least squares: comparison of objective functions for estimating linear-nonlinear models NIPS 2007
SpAM: Sparse Additive Models NIPS 2007
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization NIPS 2007
Online Linear Regression and Its Application to Model-Based Reinforcement Learning NIPS 2007
Active Preference Learning with Discrete Choice Data NIPS 2007
A Spectral Regularization Framework for Multi-Task Structure Learning NIPS 2007
Catching Change-points with Lasso NIPS 2007