2026
Resurfacing the Instance-only Dependent Label Noise Model through Loss Correction
ICLR 2026poster
We investigate the label noise problem in supervised binary classification settings and resurface the underutilized instance-_only_ dependent noise model through loss correction. On the one hand, based on risk equivalence, the instance-aware loss correction scheme completes the bridge from _empirica…