classification calibration

On Classification-Calibration of Gamma-Phi Losses COLT 2023 Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification ICML 2021 On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective CVPR 2021 On Symmetric Losses for Learning from Corrupted Labels ICML 2019 Learning with Average Top-k Loss NeurIPS 2017 Composite Multiclass Losses JMLR 2016 Convex Calibration Dimension for Multiclass Loss Matrices JMLR 2016 Consistency of structured output learning with missing labels ACML 2015 Classification Calibration Dimension for General Multiclass Losses NeurIPS 2012 Proper losses for learning from partial labels NeurIPS 2012 Composite Multiclass Losses NeurIPS 2011 Composite Binary Losses JMLR 2010 On the Efficient Minimization of Classification Calibrated Surrogates NeurIPS 2008