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Taiji Suzuki

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#machine learning Preprint Oct 2026

Finite-Sample Approximation of Hessian-Guided Perturbed Wasserstein Gradient Flows

Wasserstein gradient flow extends gradient descent to probability measures. Its Hessian-guided perturbed variant (PWGF) adds Gaussian perturbations to escape saddle points in nonconvex problems. We investigate when its approximation by finitely many interacting particles remains accurate over growing time horizons. Our...

Ryotaro Kawata, Atsushi Nitanda, Taiji Suzuki · 0 citations

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