Paper

Variance reduction for Langevin Monte Carlo in high dimensional sampling problems

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 slow convergence rate, the Langevin Monte Carlo (LMC) that provides fast convergence requires the computation of gradients... (read more)

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