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Reflected Proximal Dynamics for Accelerated High-Accuracy Log-Concave Sampling

Yuan, Bo et al.
arXiv (All) · Papers
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machine-learningstatistics-theory
We study sampling from $π(x)\propto\mathrm{e}^{-V(x)}$ on $\mathbb{R}^d$, where $V$ is $α$-strongly convex and $β$-smooth with condition number $κ=β/α$. For this problem, the proximal sampler preserves the target exactly and recovers overdamped Langevin dynamics in the small-step limit, but its Gaus
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