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Loss Functions

1162 directly classified papers

Papers per year

Papers

On the Efficient Minimization of Classification Calibrated Surrogates NIPS 2008
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost NIPS 2008
Support Vector Machines with a Reject Option NIPS 2008
Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data JMLR 2007
Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression JMLR 2007
Stagewise Lasso JMLR 2007
How SVMs can estimate quantiles and the median NIPS 2007
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006
Learning to Rank with Nonsmooth Cost Functions NIPS 2006
Considering Cost Asymmetry in Learning Classifiers JMLR 2006
Smooth ε-Insensitive Regression by Loss Symmetrization JMLR 2005
On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition JMLR 2004