Regularization

Dirty Statistical Models NeurIPS 2013 Dropout Training as Adaptive Regularization NeurIPS 2013 Estimating LASSO Risk and Noise Level NeurIPS 2013 Generalizing Analytic Shrinkage for Arbitrary Covariance Structures NeurIPS 2013 Learning with Noisy Labels NeurIPS 2013 On Decomposing the Proximal Map NeurIPS 2013 Reconciling "priors" & "priors" without prejudice? NeurIPS 2013 Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima NeurIPS 2013 The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited NeurIPS 2013 Understanding Dropout NeurIPS 2013 Calibrated Elastic Regularization in Matrix Completion NeurIPS 2012 Matrix reconstruction with the local max norm NeurIPS 2012 Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NeurIPS 2012 Parametric Local Metric Learning for Nearest Neighbor Classification NeurIPS 2012 Sparse Prediction with the k-Support Norm NeurIPS 2012 Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes NeurIPS 2012 The representer theorem for Hilbert spaces: a necessary and sufficient condition NeurIPS 2012 Transelliptical Graphical Models NeurIPS 2012 Volume Regularization for Binary Classification NeurIPS 2012 Improving Topic Coherence with Regularized Topic Models NeurIPS 2011 Phase transition in the family of p-resistances NeurIPS 2011 Regularized Laplacian Estimation and Fast Eigenvector Approximation NeurIPS 2011 Shaping Level Sets with Submodular Functions NeurIPS 2011 Trace Lasso: a trace norm regularization for correlated designs NeurIPS 2011 A Dirty Model for Multi-task Learning NeurIPS 2010