Calibrated alpha-Barycenters for Multiobjective f-Divergence Optimization
CAL-alpha-MODM addresses multiobjective optimization by aggregating a nonlinear predictor into a single barycenter and calibrating its residuals against an f-divergence objective. This allows for robust parameter error control without requiring targets to be close to the model. The method achieves cubic convergence under common matching and provides significant speedups on large target sets.