86 citations · 333 across the 21 of their papers we have counts for
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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…
Ensemble Kalman Inversion for nonlinear problems: weights, consistency, and variance bounds
Zhiyan Ding, Qin Li, Jianfeng Lu
Ensemble Kalman Inversion (EnKI) and Ensemble Square Root Filter (EnSRF) are popular sampling methods for obtaining a target posterior distribution. They can be seem as one step (t…