2 citations · 3 across the 5 of their papers we have counts for
6 papers
Strict Kantorovich contractions for Markov chains and Euler schemes with general noise
Lu-Jing Huang, Mateusz B. Majka, Jian Wang
We study contractions of Markov chains on general metric spaces with respect to some carefully designed distance-like functions, which are comparable to the total variation and the…
Variational principles for asymptotic variance of general Markov processes
Lu-Jing Huang, Yong-Hua Mao, Tao Wang
A variational formula for the asymptotic variance of general Markov processes is obtained. As application, we get a upper bound of the mean exit time of reversible Markov processes…
Variational Formulas of Asymptotic Variance for General Discrete-time Markov Chains
Lu-Jing Huang, Yong-Hua Mao
The asymptotic variance is an important criterion to evaluate the performance of Markov chains, especially for the central limit theorems. We give the variational formulas for the…
Approximation of heavy-tailed distributions via stable-driven SDEs
Lu-Jing Huang, Mateusz B. Majka, Jian Wang
Constructions of numerous approximate sampling algorithms are based on the well-known fact that certain Gibbs measures are stationary distributions of ergodic stochastic differenti…
Capacity and Exit Time for Non-reversible Diffusions
Lu-Jing Huang, Kyung-Youn Kim
Capacity is an important quantity in potential theory and in the study of Markov processes. We give equivalent conditions between the capacity, the mean exit time, and the Green fu…
On hitting time, mixing time and geometric interpretations of Metropolis-Hastings reversiblizations
Michael C. H. Choi, Lu-Jing Huang
Given a target distribution and a proposal chain with generator on a finite state space, in this paper we study two types of Metropolis-Hastings (MH) generator a…