Fisher information lower bounds for sampling

5 October 2022

Papers citing "Fisher information lower bounds for sampling"

27 / 27 papers shown

Title
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 215 131 0 26 Sep 2022
Convergence for score-based generative modeling with polynomial complexity Holden Lee Jianfeng Lu Yixin Tan DiffM 40 130 0 13 Jun 2022
Private Convex Optimization via Exponential Mechanism Sivakanth Gopi Y. Lee Daogao Liu 100 54 0 01 Mar 2022
Improved analysis for a proximal algorithm for sampling Yongxin Chen Sinho Chewi Adil Salim Andre Wibisono 58 55 0 13 Feb 2022
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo Krishnakumar Balasubramanian Sinho Chewi Murat A. Erdogdu Adil Salim Matthew Shunshi Zhang 83 62 0 10 Feb 2022
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 59 5 0 20 Jan 2022
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling Keru Wu S. Schmidler Yuansi Chen 74 54 0 27 Sep 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions Y. Lee Ruoqi Shen Kevin Tian 40 20 0 10 Jun 2021
The query complexity of sampling from strongly log-concave distributions in one dimension Sinho Chewi P. Gerber Chen Lu Thibaut Le Gouic Philippe Rigollet 65 21 0 29 May 2021
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm Sinho Chewi Chen Lu Kwangjun Ahn Xiang Cheng Thibaut Le Gouic Philippe Rigollet 41 66 0 23 Dec 2020
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 75 36 0 19 Oct 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 36 76 0 27 May 2020
Oracle Lower Bounds for Stochastic Gradient Sampling Algorithms Niladri S. Chatterji Peter L. Bartlett Philip M. Long 16 8 0 01 Feb 2020
How to trap a gradient flow Sébastien Bubeck Dan Mikulincer 23 12 0 09 Jan 2020
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds Rong Ge Holden Lee Jianfeng Lu 27 22 0 08 Nov 2019
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 104 49 0 04 Nov 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 31 71 0 19 Jun 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices Santosh Vempala Andre Wibisono 41 262 0 20 Mar 2019
Non-asymptotic bounds for sampling algorithms without log-concavity Mateusz B. Majka Aleksandar Mijatović Lukasz Szpruch 29 73 0 21 Aug 2018
Sharp convergence rates for Langevin dynamics in the nonconvex setting Xiang Cheng Niladri S. Chatterji Yasin Abbasi-Yadkori Peter L. Bartlett Michael I. Jordan 43 166 0 04 May 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 71 178 0 22 Feb 2018
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD Zeyuan Allen-Zhu ODL 48 169 0 08 Jan 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo Rong Ge Holden Lee Andrej Risteski 61 54 0 07 Oct 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization Pan Xu Jinghui Chen Difan Zou Quanquan Gu 47 202 0 20 Jul 2017
Underdamped Langevin MCMC: A non-asymptotic analysis Xiang Cheng Niladri S. Chatterji Peter L. Bartlett Michael I. Jordan 72 296 0 12 Jul 2017
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 66 351 0 05 May 2016
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 48 410 0 17 Jul 2015