47 citations · 317 across the 48 of their papers we have counts for
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Constrained Ensemble Langevin Monte Carlo
Zhiyan Ding, Qin Li
The classical Langevin Monte Carlo method looks for samples from a target distribution by descending the samples along the gradient of the target distribution. The method enjoys a…
Random Coordinate Underdamped Langevin Monte Carlo
Zhiyan Ding, Qin Li, Jianfeng Lu +1
The Underdamped Langevin Monte Carlo (ULMC) is a popular Markov chain Monte Carlo sampling method. It requires the computation of the full gradient of the log-density at each itera…
Random Coordinate Langevin Monte Carlo
Zhiyan Ding, Qin Li, Jianfeng Lu +1
Langevin Monte Carlo (LMC) is a popular Markov chain Monte Carlo sampling method. One drawback is that it requires the computation of the full gradient at each iteration, an expens…
Langevin Monte Carlo: random coordinate descent and variance reduction
Zhiyan Ding, Qin Li
Langevin Monte Carlo (LMC) is a popular Bayesian sampling method. For the log-concave distribution function, the method converges exponentially fast, up to a controllable discretiz…
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo
Zhiyan Ding, Qin Li
Sampling from a log-concave distribution function is one core problem that has wide applications in Bayesian statistics and machine learning. While most gradient free methods have…