Sinho Chewi | DeepAI

AI Chat

Featured Co-authors

Yi Zhang
258 publications
Francis Bach
160 publications
Jianfeng Lu
98 publications
Yuanzhi Li
85 publications
Yin Tat Lee
64 publications
Jerry Li
59 publications
Sébastien Bubeck
54 publications
Kannan Ramchandran
53 publications
Philippe Rigollet
46 publications
Yongxin Chen
45 publications
Krishnakumar Balasubramanian
44 publications

∙ 05/19/2023

The probability flow ODE is provably fast

We provide the first polynomial-time convergence guarantees for the prob...

0 Sitan Chen, et al. ∙

∙ 04/10/2023

Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space

Variational inference (VI) seeks to approximate a target distribution π ...

7 Michael Diao, et al. ∙

∙ 04/05/2023

Query lower bounds for log-concave sampling

Log-concave sampling has witnessed remarkable algorithmic advances in re...

0 Sinho Chewi, et al. ∙

∙ 02/20/2023

Faster high-accuracy log-concave sampling via algorithmic warm starts

Understanding the complexity of sampling from a strongly log-concave and...

0 Jason M. Altschuler, et al. ∙

∙ 02/16/2023

Improved Discretization Analysis for Underdamped Langevin Monte Carlo

Underdamped Langevin Monte Carlo (ULMC) is an algorithm used to sample f...

0 Matthew Zhang, et al. ∙

∙ 12/14/2022

Learning threshold neurons via the "edge of stability"

Existing analyses of neural network training often operate under the unr...

0 Kwangjun Ahn, et al. ∙

∙ 10/05/2022

Fisher information lower bounds for sampling

We prove two lower bounds for the complexity of non-log-concave sampling...

0 Sinho Chewi, et al. ∙

∙ 09/22/2022

Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

We provide theoretical convergence guarantees for score-based generative...

1 Sitan Chen, et al. ∙

∙ 05/31/2022

Variational inference via Wasserstein gradient flows

Along with Markov chain Monte Carlo (MCMC) methods, variational inferenc...

0 Marc Lambert, et al. ∙

∙ 03/09/2022

An entropic generalization of Caffarelli's contraction theorem via covariance inequalities

The optimal transport map between the standard Gaussian measure and an α...

0 Sinho Chewi, et al. ∙

∙ 02/13/2022

Improved analysis for a proximal algorithm for sampling

We study the proximal sampler of Lee, Shen, and Tian (2021) and obtain n...

0 Yongxin Chen, et al. ∙

∙ 02/10/2022

Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo

For the task of sampling from a density π∝exp(-V) on ℝ^d, where V is pos...

6 Krishnakumar Balasubramanian, et al. ∙

∙ 12/23/2021

Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev

Classically, the continuous-time Langevin diffusion converges exponentia...

0 Sinho Chewi, et al. ∙

∙ 12/21/2021

The entropic barrier is n-self-concordant

For any convex body K ⊆ℝ^n, S. Bubeck and R. Eldan introduced the entrop...

0 Sinho Chewi, et al. ∙

∙ 09/17/2021

Gaussian discrepancy: a probabilistic relaxation of vector balancing

We introduce a novel relaxation of combinatorial discrepancy called Gaus...

0 Sinho Chewi, et al. ∙

∙ 06/16/2021

Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent

We study first-order optimization algorithms for computing the barycente...

0 Jason M. Altschuler, et al. ∙

∙ 05/29/2021

Rejection sampling from shape-constrained distributions in sublinear time

We consider the task of generating exact samples from a target distribut...

0 Sinho Chewi, et al. ∙

∙ 05/29/2021

The query complexity of sampling from strongly log-concave distributions in one dimension

We establish the first tight lower bound of Ω(loglogκ) on the query comp...

0 Sinho Chewi, et al. ∙

∙ 12/23/2020

Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm

Conventional wisdom in the sampling literature, backed by a popular diff...

0 Sinho Chewi, et al. ∙

∙ 10/30/2020

Efficient constrained sampling via the mirror-Langevin algorithm

We propose a new discretization of the mirror-Langevin diffusion and giv...

0 Kwangjun Ahn, et al. ∙

∙ 10/22/2020

Fast and Smooth Interpolation on Wasserstein Space

We propose a new method for smoothly interpolating probability measures ...

0 Sinho Chewi, et al. ∙

∙ 06/03/2020

SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence

Stein Variational Gradient Descent (SVGD), a popular sampling algorithm,...

0 Sinho Chewi, et al. ∙

∙ 05/19/2020

Exponential ergodicity of mirror-Langevin diffusions

Motivated by the problem of sampling from ill-conditioned log-concave di...

0 Sinho Chewi, et al. ∙

∙ 01/06/2020

Gradient descent algorithms for Bures-Wasserstein barycenters

We study first order methods to compute the barycenter of a probability ...

0 Sinho Chewi, et al. ∙

∙ 06/18/2018

Online Absolute Ranking with Partial Information: A Bipartite Graph Matching Approach

Ever since the introduction of the secretary problem, the notion of sele...

0 Sinho Chewi, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world