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Lukang Sun

2 accepted papers

2023

Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition

AISTATS 2023poster

Stein Variational Gradient Descent (SVGD) is an important alternative to the Langevin-type algorithms for sampling from probability distributions of the form $\pi(x) \propto \exp(-V(x))$. In the existing theory of Langevin-type algorithms and SVGD, the potential function $V$ is often assumed to be $…

Cited by 21SourcePDFScholar
2022

A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1

ICML 2022spotlight

Stein Variational Gradient Descent (SVGD) is an algorithm for sampling from a target density which is known up to a multiplicative constant. Although SVGD is a popular algorithm in practice, its theoretical study is limited to a few recent works. We study the convergence of SVGD in the population li…

Cited by 27SourcePDFScholar