loss function

Approximate inference for the loss-calibrated Bayesian AISTATS 2011 Composite Multiclass Losses NeurIPS 2011 Large-Scale Category Structure Aware Image Categorization NeurIPS 2011 Relaxed Clipping: A Global Training Method for Robust Regression and Classification NeurIPS 2010 Static Analysis of Binary Executables Using Structural SVMs NeurIPS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 Variable margin losses for classifier design NeurIPS 2010 Distribution-Calibrated Hierarchical Classification NeurIPS 2009 Ranking Measures and Loss Functions in Learning to Rank NeurIPS 2009 On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost NeurIPS 2008 On the Efficient Minimization of Classification Calibrated Surrogates NeurIPS 2008 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006 Incremental Algorithms for Hierarchical Classification JMLR 2006 A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs JMLR 2005 Smooth ε-Insensitive Regression by Loss Symmetrization JMLR 2005