4 papers
Variance Reduction for Stochastic Gradient Generalized Non-reversible Langevin Monte Carlo Algorithms
Bingye Ni, Xiaoyu Wang, Yingli Wang +1
We study the leading-order fluctuation of stochastic gradient Euler-Maruyama estimators for generalized non-reversible Langevin dynamics. Under structural assumptions tailored to t…
Sampling non-log-concave densities via Hessian-free high-resolution dynamics
Xiaoyu Wang, Yingli Wang, Lingjiong Zhu
We study the problem of sampling from a target distribution on , where can be non-convex, via the Hessian-free high-resolution (HFHR) dyna…
Regime-Switching Langevin Monte Carlo Algorithms
Xiaoyu Wang, Yingli Wang, Lingjiong Zhu
Langevin Monte Carlo (LMC) algorithms are popular Markov Chain Monte Carlo (MCMC) methods to sample a target probability distribution, which arises in many applications in machine…
Rough Heston model as the scaling limit of bivariate cumulative heavy-tailed INAR processes: Weak-error bounds and option pricing
Yingli Wang, Zhenyu Cui, Lingjiong Zhu
We study nearly unstable bivariate cumulative heavy-tailed INAR() processes and show that, under a one-factor parameterization and a suitable scaling, they converge to the…