2 papers
cs.LG2026
Bayes-Optimal BER and AUC: Estimation and Evaluation of Estimators
Ryota Ushio, Takashi Ishida, Masashi Sugiyama
A fundamental quantity in machine learning is the optimal performance achievable by any model on a given task. Estimating this quantity allows us to distinguish the irreducible par…
cs.LG2025
Practical estimation of the optimal classification error with soft labels and calibration
Ryota Ushio, Takashi Ishida, Masashi Sugiyama
While the performance of machine learning systems has experienced significant improvement in recent years, relatively little attention has been paid to the fundamental question: to…