论文标题
关于镜像的Stein变化梯度下降下降（l_0，l_1） - $平滑度条件下的镜像变化梯度下降的注释
A Note on the Convergence of Mirrored Stein Variational Gradient Descent under $(L_0,L_1)-$Smoothness Condition
论文作者
论文摘要
在本说明中，我们建立了种群极限的下降引理，反映了Stein变异梯度方法〜（MSVGD）。此下降引理不依赖MSVGD的路径信息，而是对镜像分布的简单假设$ \nablaψ_ {\＃}π\ propto \ exp（-v）$。我们的分析表明，MSVGD可以应用于非平滑$ V $的更广泛的约束采样问题。我们还研究人口的复杂性限制了MSVGD的尺寸$ d $。
In this note, we establish a descent lemma for the population limit Mirrored Stein Variational Gradient Method~(MSVGD). This descent lemma does not rely on the path information of MSVGD but rather on a simple assumption for the mirrored distribution $\nablaΨ_{\#}π\propto\exp(-V)$. Our analysis demonstrates that MSVGD can be applied to a broader class of constrained sampling problems with non-smooth $V$. We also investigate the complexity of the population limit MSVGD in terms of dimension $d$.
