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Loss Functions

1162 directly classified papers

Papers per year

Papers

Learning Structured Models with the AUC Loss and Its Generalizations AISTATS 2014
On Robustness and Regularization of Structural Support Vector Machines ICML 2014
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models ICML 2014
One Millisecond Face Alignment with an Ensemble of Regression Trees CVPR 2014
Consistent Binary Classification with Generalized Performance Metrics NIPS 2014
Deep Boosting ICML 2014
Elicitation and Identification of Properties COLT 2014
The Coherent Loss Function for Classification ICML 2014
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance ICML 2013
Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems JMLR 2013
Cost-sensitive Multiclass Classification Risk Bounds ICML 2013
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses NIPS 2013
Loss-Proportional Subsampling for Subsequent ERM ICML 2013
Perceptual Fidelity Aware Mean Squared Error ICCV 2013
Structured Learning via Logistic Regression NIPS 2013
Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper Losses COLT 2013
Accuracy at the Top NIPS 2012
On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking NIPS 2012
Learning from the Wisdom of Crowds by Minimax Entropy NIPS 2012
Learning Low-order Models for Enforcing High-order Statistics AISTATS 2012
Persistent Homology for Learning Densities with Bounded Support NIPS 2012
Classification Calibration Dimension for General Multiclass Losses NIPS 2012
Proper losses for learning from partial labels NIPS 2012
A Unified View of Performance Metrics: Translating Threshold Choice into Expected Classification Loss JMLR 2012
A Characterization of Scoring Rules for Linear Properties COLT 2012