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#machine learning Preprint Sep 2026

Sharp Convergence and Sampling Trade-offs for Riemannian Diffusion under Nonnegative Ricci Curvature

Diffusion models have emerged as state-of-the-art generative models, with recent extensions from Euclidean spaces to Riemannian manifolds. However, existing convergence guarantees for Riemannian diffusion models typically require $\tilde{O}(\mathrm{poly}(d,T)/\epsilon^2)$ score evaluations, with potentially unfavorable...

Yu-Hao Liu, Long-Bo Huang · 0 citations
Preprint Aug 2026

Lipschitz Bandits with Arbitrary Feedback Delays

The authors' bounds match existing delay-free regret guarantees for Lipschitz bandits and characterize the additional $\tilde{O}(\sqrt{D})$ impact introduced by feedback delays.

Yu-Hao Liu, Yu Chen, Long-Bo Huang · 0 citations

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