1 citations · 1 across the 8 of their papers we have counts for
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High-dimensional normal approximations for sums of Langevin Markov chains
Tian Shen, Zhonggen Su, Xiaolin Wang
Consider the well-known Langevin diffusion on and its Euler-Maruyama discretization give…
Convergence rate of randomized midpoint Langevin Monte Carlo
Ruinan Li, Tian Shen, Zhonggen Su
The randomized midpoint Langevin Monte Carlo (RLMC), introduced by Shen and Lee (2019), is a variant of classical Unadjusted Langevin Algorithm. It was shown in the literature that…
Non-asymptotic Analysis of Poisson randomized midpoint Langevin Monte Carlo
Tian Shen, Zhonggen Su
The task of sampling from a high-dimensional distribution on is a fundamental algorithmic problem with applications throughout statistics, engineering, and the sciences.…
Geo-R1: Improving Few-Shot Geospatial Referring Expression Understanding with Reinforcement Fine-Tuning
Zilun Zhang, Zian Guan, Tiancheng Zhao +7
Referring expression understanding in remote sensing poses unique challenges, as it requires reasoning over complex object-context relationships. While supervised fine-tuning (SFT)…
Conditional central limit theorems for exponential random graphs
Xiao Fang, Song-Hao Liu, Zhonggen Su +1
In this paper, we study the Exponential Random Graph Models (ERGMs) conditioning on the number of edges. In subcritical region of model parameters, we prove a conditional Central L…