English(EN) Anchored Stein Variational Gradient Descent Algorithm for Non-smooth Sampling

开发出用于非光滑采样的新锚定SVGD算法

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

研究人员开发了一种名为锚定Stein变分梯度下降（SVGD）的新算法，用于从可能非光滑的目标密度进行采样。该方法引入了一个更光滑的参考势能和一个锚定权重，使其能够在不直接计算非光滑势能梯度的情况下对密度进行采样。该算法已被证明在低正则性条件下收敛，并基于锚定核化Stein差异提供了非渐近界。 AI

影响为机器学习中的采样引入了一种新颖的算法方法，有可能在处理复杂、非光滑概率分布时提高性能。

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arXiv stat.ML TIER_1 English(EN) · Thanh Dang, Matthew X. Burns, Jiaming Liang · 2026-10-28 04:00

非光滑采样锚定Stein变分梯度下降算法

arXiv:2610.36018v1 Announce Type: new Abstract: We introduce a Stein variational framework for sampling from a target density $p\propto e^{-U}$ when the target potential $U$ is possibly non-smooth. The key idea is to introduce a smoother reference potential $U_0$ and the anchor w…