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most citedConvergence Rates of Gradient Methods for Convex Optimization in the Space of Measures

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math.AP2026

Quantitative Convergence of Wasserstein Gradient Flows of Kernel Mean Discrepancies

Lénaïc Chizat, Maria Colombo, Roberto Colombo +1

We study the quantitative convergence of Wasserstein gradient flows of Kernel Mean Discrepancy (KMD) (also known as Maximum Mean Discrepancy (MMD)) functionals. Our setting covers…