Paper

Stability and Generalization of Learning Algorithms that Converge to Global Optima

We establish novel generalization bounds for learning algorithms that converge to global minima. We do so by deriving black-box stability results that only depend on the convergence of a learning algorithm and the geometry around the minimizers of the loss function... (read more)

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