empirical risk minimization

Accelerated Mini-batch Randomized Block Coordinate Descent Method NeurIPS 2014 Altitude Training: Strong Bounds for Single-Layer Dropout NeurIPS 2014 An Accelerated Proximal Coordinate Gradient Method NeurIPS 2014 An Inequality with Applications to Structured Sparsity and Multitask Dictionary Learning COLT 2014 From Stochastic Mixability to Fast Rates NeurIPS 2014 Large-scale Multi-label Learning with Missing Labels ICML 2014 Learnability of the Superset Label Learning Problem ICML 2014 Learning without concentration COLT 2014 Optimal learners for multiclass problems COLT 2014 Boosting with the Logistic Loss is Consistent COLT 2013 Characterizing the Representer Theorem ICML 2013 Learning with Noisy Labels NeurIPS 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Loss-Proportional Subsampling for Subsequent ERM ICML 2013 Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013 A Primal-Dual Convergence Analysis of Boosting JMLR 2012 Local Supervised Learning through Space Partitioning NeurIPS 2012 Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL NeurIPS 2012 Multi-Stage Classifier Design ACML 2012 Private Convex Empirical Risk Minimization and High-dimensional Regression COLT 2012 Regularized Bundle Methods for Convex and Non-Convex Risks JMLR 2012 Differentially Private Empirical Risk Minimization JMLR 2011 Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011 Multiclass Learnability and the ERM principle COLT 2011 Oracle inequalities for computationally budgeted model selection COLT 2011