confusion matrix

Confusion-Aware Spectral Regularizer for Long-Tailed Recognition CVPR 2026 DS-Compatible Log-Linear Reliability with KL-Prox EM: Monotone Ascent, Identifiability, and Generalization ALT 2026 Enhancing Robust Fairness via Confusional Spectral Regularization ICLR 2025 Of Dice and Games: A Theory of Generalized Boosting COLT 2025 A General Online Algorithm for Optimizing Complex Performance Metrics ICML 2024 Consistent Multiclass Algorithms for Complex Metrics and Constraints JMLR 2024 Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound NeurIPS 2024 Coupled Confusion Correction: Learning from Crowds with Sparse Annotations AAAI 2024 Generative Calibration of Inaccurate Annotation for Label Distribution Learning AAAI 2024 Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom NeurIPS 2024 On Truthing Issues in Supervised Classification JMLR 2024 Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results AISTATS 2024 Never mind the metrics---what about the uncertainty? Visualising binary confusion matrix metric distributions to put performance in perspective ICML 2023 Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers NeurIPS 2022 Group-Aware Threshold Adaptation for Fair Classification AAAI 2022 How Did the Model Change? Efficiently Assessing Machine Learning API Shifts ICLR 2022 Optimal Binary Classification Beyond Accuracy NeurIPS 2022 Relieving Long-Tailed Instance Segmentation via Pairwise Class Balance CVPR 2022 The Hitchhiker's Guide to Prior-Shift Adaptation WACV 2022 Optimizing Black-box Metrics with Iterative Example Weighting ICML 2021 Adversarial-Learned Loss for Domain Adaptation AAAI 2020 A Unified View of Label Shift Estimation NeurIPS 2020 Consistent Plug-in Classifiers for Complex Objectives and Constraints NeurIPS 2020 FACT: A Diagnostic for Group Fairness Trade-offs ICML 2020 Reinforcement Learning with Perturbed Rewards AAAI 2020