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The asymptotic behavior of RBF kernel MLEs is finally understood, revealing minimax optimal convergence rates for all key parameters.
Despite the growing concern of model collapse due to AI-generated data contaminating training sets, this work shows that generative models can still converge under recursive training with provable guarantees.
