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math.ST2020★ 8 cited
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm
Sinho Chewi, Chen Lu, Kwangjun Ahn +3
Conventional wisdom in the sampling literature, backed by a popular diffusion scaling limit, suggests that the mixing time of the Metropolis-Adjusted Langevin Algorithm (MALA) scal…
math.ST2019★ 3 cited
Quantitative Weak Convergence for Discrete Stochastic Processes
Xiang Cheng, Peter L. Bartlett, Michael I. Jordan
In this paper, we quantitative convergence in for a family of Langevin-like stochastic processes that includes stochastic gradient descent and related gradient-based algorith…