Loss Functions

Consistent Binary Classification with Generalized Performance Metrics NeurIPS 2014 Deep Boosting ICML 2014 Elicitation and Identification of Properties COLT 2014 GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare ICML 2014 Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting ICML 2014 Learning Structured Models with the AUC Loss and Its Generalizations AISTATS 2014 One Millisecond Face Alignment with an Ensemble of Regression Trees CVPR 2014 On Robustness and Regularization of Structural Support Vector Machines ICML 2014 Optimizing F-Measures by Cost-Sensitive Classification NeurIPS 2014 Sample-based approximate regularization ICML 2014 Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses JMLR 2014 The Coherent Loss Function for Classification ICML 2014 The Geometry of Losses COLT 2014 The limits of squared Euclidean distance regularization NeurIPS 2014 Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets NeurIPS 2014 Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models ICML 2014 Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems JMLR 2013 Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses NeurIPS 2013 Cost-sensitive Multiclass Classification Risk Bounds ICML 2013 Loss-Proportional Subsampling for Subsequent ERM ICML 2013 On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance ICML 2013 Perceptual Fidelity Aware Mean Squared Error ICCV 2013 Structured Learning via Logistic Regression NeurIPS 2013 Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper Losses COLT 2013 Accuracy at the Top NeurIPS 2012