LWCal: Loss-Weighted Calibration for Tabular Classifiers with Noisy Calibration Labels
arXiv:2609.26839v1 Announce Type: new Abstract: Post-hoc probability calibration is usually evaluated under an optimistic assumption: the held-out calibration labels are clean. In many AI deployment settings, however, labels come from weak annotators, historical decisions, heuristics, or distant su…
Read the full story at arXiv cs.LG ↗
Timeline · 1 report
- 2026-09-24 04:00 · arXiv cs.LG
LWCal: Loss-Weighted Calibration for Tabular Classifiers with Noisy Calibration Labels