7 citations · 18 across the 5 of their papers we have counts for
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cs.LG2021★ 5 cited
Sqrt(d) Dimension Dependence of Langevin Monte Carlo
Ruilin Li, Hongyuan Zha, Molei Tao
This article considers the popular MCMC method of unadjusted Langevin Monte Carlo (LMC) and provides a non-asymptotic analysis of its sampling error in 2-Wasserstein distance. The…
cs.LG2020★ 3 cited
Hessian-Free High-Resolution Nesterov Acceleration for Sampling
Ruilin Li, Hongyuan Zha, Molei Tao
Nesterov's Accelerated Gradient (NAG) for optimization has better performance than its continuous time limit (noiseless kinetic Langevin) when a finite step-size is employed \citep…
cs.LG2020
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients
Ruilin Li, Xin Wang, Hongyuan Zha +1
Many Markov Chain Monte Carlo (MCMC) methods leverage gradient information of the potential function of target distribution to explore sample space efficiently. However, computing…