15 citations · 38 across the 12 of their papers we have counts for
7 papers · 1 filter
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…
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…
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
Sinho Chewi, Thibaut Le Gouic, Chen Lu +2
Stein Variational Gradient Descent (SVGD), a popular sampling algorithm, is often described as the kernelized gradient flow for the Kullback-Leibler divergence in the geometry of o…
Exponential ergodicity of mirror-Langevin diffusions
Sinho Chewi, Thibaut Le Gouic, Chen Lu +3
Motivated by the problem of sampling from ill-conditioned log-concave distributions, we give a clean non-asymptotic convergence analysis of mirror-Langevin diffusions as introduced…
Convergence rates for empirical barycenters in metric spaces: curvature, convexity and extendible geodesics
Adil Ahidar-Coutrix, Thibaut Le Gouic, Quentin Paris
This paper provides rates of convergence for empirical (generalised) barycenters on compact geodesic metric spaces under general conditions using empirical processes techniques. Ou…