2026
MoE^2: A Mixture-of-Mixtures of Experts for Ensemble-Free Domain Generalization
AAAI 2026technical
Domain Generalization (DG) requires models to generalize across unseen data distributions. Kernel-based theory reveals a No-Free-Lunch problem: any model with a fixed representation is fundamentally sub-optimal for all possible shifts. While large ensembles mitigate this, they are computationally ex