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Loss Functions

1162 directly classified papers

Papers per year

Papers

A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems COLT 2012
Selective Labeling via Error Bound Minimization NIPS 2012
Multiclass Boosting: Theory and Algorithms NIPS 2011
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss NIPS 2011
Neyman-Pearson Classification, Convexity and Stochastic Constraints JMLR 2011
Composite Multiclass Losses NIPS 2011
Semi-supervised Learning by Higher Order Regularization AISTATS 2011
A concave regularization technique for sparse mixture models NIPS 2011
Approximate inference for the loss-calibrated Bayesian AISTATS 2011
Variance Penalizing AdaBoost NIPS 2011
Efficient variable selection in support vector machines via the alternating direction method of multipliers AISTATS 2011
Trace Lasso: a trace norm regularization for correlated designs NIPS 2011
Mixability is Bayes Risk Curvature Relative to Log Loss COLT 2011
Classification Methods with Reject Option Based on Convex Risk Minimization JMLR 2010
Empirical Bernstein Boosting AISTATS 2010
Variable margin losses for classifier design NIPS 2010
Regularized estimation of image statistics by Score Matching NIPS 2010
Maximum Relative Margin and Data-Dependent Regularization JMLR 2010
Convexity of Proper Composite Binary Losses AISTATS 2010
Relaxed Clipping: A Global Training Method for Robust Regression and Classification NIPS 2010
Distribution-Calibrated Hierarchical Classification NIPS 2009
Ranking Measures and Loss Functions in Learning to Rank NIPS 2009
Learning Nondeterministic Classifiers JMLR 2009
Learning to Rank by Optimizing NDCG Measure NIPS 2009
From PAC-Bayes Bounds to KL Regularization NIPS 2009