Regularization

A Family of Penalty Functions for Structured Sparsity NeurIPS 2010 Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010 Learning Multiple Tasks using Manifold Regularization NeurIPS 2010 Linear Complementarity for Regularized Policy Evaluation and Improvement NeurIPS 2010 Regularized estimation of image statistics by Score Matching NeurIPS 2010 Spatial and anatomical regularization of SVM for brain image analysis NeurIPS 2010 Spectral Regularization for Support Estimation NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NeurIPS 2010 Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework NeurIPS 2010 Adaptive Regularization for Transductive Support Vector Machine NeurIPS 2009 Adaptive Regularization of Weight Vectors NeurIPS 2009 Asymptotically Optimal Regularization in Smooth Parametric Models NeurIPS 2009 A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers NeurIPS 2009 Boosting with Spatial Regularization NeurIPS 2009 From PAC-Bayes Bounds to KL Regularization NeurIPS 2009 High-dimensional support union recovery in multivariate regression NeurIPS 2008 Learning with Consistency between Inductive Functions and Kernels NeurIPS 2008 Multi-stage Convex Relaxation for Learning with Sparse Regularization NeurIPS 2008 Nonparametric regression and classification with joint sparsity constraints NeurIPS 2008 On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization NeurIPS 2008 Regularized Learning with Networks of Features NeurIPS 2008 Regularized Policy Iteration NeurIPS 2008 A Spectral Regularization Framework for Multi-Task Structure Learning NeurIPS 2007 Bundle Methods for Machine Learning NeurIPS 2007 Classification via Minimum Incremental Coding Length (MICL) NeurIPS 2007