Loss Functions

Linking losses for density ratio and class-probability estimation ICML 2016 Loss factorization, weakly supervised learning and label noise robustness ICML 2016 Loss Functions for Top-k Error: Analysis and Insights CVPR 2016 On Regularizing Rademacher Observation Losses NeurIPS 2016 On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting JMLR 2016 Optimal Classification with Multivariate Losses ICML 2016 Temporal Action Localization in Untrimmed Videos via Multi-Stage CNNs CVPR 2016 A New Generalized Error Path Algorithm for Model Selection ICML 2015 A View of Margin Losses as Regularizers of Probability Estimates JMLR 2015 Calibrated Structured Prediction NeurIPS 2015 Convex Risk Minimization and Conditional Probability Estimation COLT 2015 Cross-Age Face Verification by Coordinating With Cross-Face Age Verification CVPR 2015 Generalized Mixability via Entropic Duality COLT 2015 Learning with Symmetric Label Noise: The Importance of Being Unhinged NeurIPS 2015 Learning with the Maximum Correntropy Criterion Induced Losses for Regression JMLR 2015 Multi-Objective Convolutional Learning for Face Labeling CVPR 2015 On Consistent Surrogate Risk Minimization and Property Elicitation COLT 2015 On Elicitation Complexity NeurIPS 2015 On the Accuracy of Self-Normalized Log-Linear Models NeurIPS 2015 On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property ICML 2015 Regularization Path of Cross-Validation Error Lower Bounds NeurIPS 2015 Robust Non-Rigid Motion Tracking and Surface Reconstruction Using L0 Regularization ICCV 2015 Self Scaled Regularized Robust Regression CVPR 2015 Surrogate regret bounds for generalized classification performance metrics ACML 2015 Total Variation Regularization of Shape Signals CVPR 2015