Author

Qian Qin

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Preprint Sep 2026

A spectral gap for Metropolis-adjusted Langevin algorithm with a uniformly randomized step size

Let $\pi(\mathrm{d} x)\propto e^{-U(x)}\, \mathrm{d} x$ on $\mathbb{R}^d$, where $U$ is continuously differentiable and $m$-strongly convex with a globally $L$-Lipschitz gradient, $0<m\leq L<\infty$, and $\kappa=L/m$. Fixed-step Metropolis-adjusted Langevin algorithm (MALA) has known warm-start mixing-time upper bounds...

Qian Qin · 0 citations

Preprint Sep 2026

A global spectral gap for Metropolis-adjusted Langevin algorithm with a uniformly randomized step size

Let $\pi(\mathrm{d} x)\propto e^{-U(x)}\,\mathrm{d} x$ on $\mathbb R^d$, where $0<m\leq L<\infty$, $mI_d\preceq\nabla^2U(x)\preceq LI_d$, and $\kappa=L/m$. It is known that, under warm-start assumptions, fixed-step Metropolis-adjusted Langevin algorithm (MALA) with properly tuned step size has mixing time of order $\ka...

Qian Qin · 0 citations