EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification

Ben Dai

Empirical risk minimization (ERM) with a computationally feasible surrogate loss is a widely accepted approach for classification. Notably, the convexity and calibration (CC) prope…