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Regression

195 directly classified papers

Papers per year

Papers

Pointwise Tracking the Optimal Regression Function NIPS 2012
Continuous-Time Regression Models for Longitudinal Networks NIPS 2011
Tight conditions for consistent variable selection in high dimensional nonparametric regression COLT 2011
Learning To Count Objects in Images NIPS 2010
Heavy-Tailed Process Priors for Selective Shrinkage NIPS 2010
Fast Active-set-type Algorithms for $l1$-regularized Linear Regression AISTATS 2010
Directed Regression NIPS 2009
Gaussian process regression with Student-t likelihood NIPS 2009
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness NIPS 2009
Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity NIPS 2009
Nonparametric Greedy Algorithms for the Sparse Learning Problem NIPS 2009
Robust Regression and Lasso NIPS 2008
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression NIPS 2007
How SVMs can estimate quantiles and the median NIPS 2007
Robust Regression with Twinned Gaussian Processes NIPS 2007
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data JMLR 2006
Mixture Regression for Covariate Shift NIPS 2006
Predicting spike times from subthreshold dynamics of a neuron NIPS 2006
Nonparametric Quantile Estimation JMLR 2006
Smooth ε-Insensitive Regression by Loss Symmetrization JMLR 2005