Faster Convergence of Stochastic Gradient Langevin Dynamics for
Non-Log-Concave Sampling

Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling

19 October 2020

Quanquan Gu

Papers citing "Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling"

11 / 11 papers shown

Title
Operator-Level Quantum Acceleration of Non-Logconcave Sampling Jiaqi Leng Zhiyan Ding Zherui Chen Lin Lin 62 0 0 08 May 2025
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 26 20 0 29 May 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 27 7 0 27 May 2023
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation David Holzmüller Francis R. Bach 29 8 0 06 Mar 2023
Geometric ergodicity of SGLD via reflection coupling Lei Li Jian‐Guo Liu Yuliang Wang 39 2 0 17 Jan 2023
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 43 15 0 05 Oct 2022
A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics Lei Li Yuliang Wang 39 11 0 19 Jul 2022
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms Aniket Das Dheeraj M. Nagaraj Anant Raj 47 6 0 08 Jun 2022
Coupling and Convergence for Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle Raphael Zimmer 77 136 0 01 May 2018
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 34 158 0 21 Oct 2016
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,262 0 09 Jun 2012