6 papers · 1 filter
High-accuracy log-concave sampling with stochastic queries
Fan Chen, Sinho Chewi, Constantinos Daskalakis +1
We show that high-accuracy guarantees for log-concave sampling -- that is, iteration and query complexities which scale as , where is the desired targ…
A proximal gradient algorithm for composite log-concave sampling
Linghai Liu, Sinho Chewi
We propose an algorithm to sample from composite log-concave distributions over , i.e., densities of the form , assuming access to gradient evalua…
Sampling from Constrained Gibbs Measures: with Applications to High-Dimensional Bayesian Inference
Ruixiao Wang, Xiaohong Chen, Sinho Chewi
This paper considers a non-standard problem of generating samples from a low-temperature Gibbs distribution with \emph{constrained} support, when some of the coordinates of the mod…
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
Yiheng Jiang, Sinho Chewi, Aram-Alexandre Pooladian
We develop a theory of finite-dimensional polyhedral subsets over the Wasserstein space and optimization of functionals over them via first-order methods. Our main application is t…
Shifted Composition III: Local Error Framework for KL Divergence
Jason M. Altschuler, Sinho Chewi
Coupling arguments are a central tool for bounding the deviation between two stochastic processes, but traditionally have been limited to Wasserstein metrics. In this paper, we app…
Sampling from the Mean-Field Stationary Distribution
Yunbum Kook, Matthew S. Zhang, Sinho Chewi +2
We study the complexity of sampling from the stationary distribution of a mean-field SDE, or equivalently, the complexity of minimizing a functional over the space of probability m…