15 citations · 30 across the 6 of their papers we have counts for
9 papers
The query complexity of sampling from strongly log-concave distributions in one dimension
Sinho Chewi, Patrik Gerber, Chen Lu +2
We establish the first tight lower bound of on the query complexity of sampling from the class of strongly log-concave and log-smooth distributions with condition nu…
Rejection sampling from shape-constrained distributions in sublinear time
Sinho Chewi, Patrik Gerber, Chen Lu +2
We consider the task of generating exact samples from a target distribution, known up to normalization, over a finite alphabet. The classical algorithm for this task is rejection s…
Dimension-free log-Sobolev inequalities for mixture distributions
Hong-Bin Chen, Sinho Chewi, Jonathan Niles-Weed
We prove that if is a family of probability measures which satisfy the log-Sobolev inequality and whose pairwise chi-squared divergences are uniformly b…
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…
Fast and Smooth Interpolation on Wasserstein Space
Sinho Chewi, Julien Clancy, Thibaut Le Gouic +3
We propose a new method for smoothly interpolating probability measures using the geometry of optimal transport. To that end, we reduce this problem to the classical Euclidean sett…
Efficient constrained sampling via the mirror-Langevin algorithm
Kwangjun Ahn, Sinho Chewi
We propose a new discretization of the mirror-Langevin diffusion and give a crisp proof of its convergence. Our analysis uses relative convexity/smoothness and self-concordance, id…