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Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients

29 May 2019

Papers citing "Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients"

36 / 36 papers shown

Title
Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality Andre Wibisono 122 1 0 01 Jul 2025
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo Haoyang Zheng Wei Deng Christian Moya Guang Lin 94 6 0 22 Jan 2024
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration Nawaf Bou-Rabee Milo Marsden 79 13 0 20 Nov 2022
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 88 12 0 13 Oct 2022
Variational inference via Wasserstein gradient flows Marc Lambert Sinho Chewi Francis R. Bach Silvère Bonnabel Philippe Rigollet BDL DRL 101 77 0 31 May 2022
Private Convex Optimization via Exponential Mechanism Sivakanth Gopi Y. Lee Daogao Liu 141 55 0 01 Mar 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 104 18 0 28 Feb 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo L. Riou-Durand Jure Vogrinc 90 15 0 26 Feb 2022
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 84 40 0 03 Feb 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 88 12 0 02 Feb 2022
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 83 5 0 20 Jan 2022
Metropolis Augmented Hamiltonian Monte Carlo Guangyao Zhou 80 1 0 20 Jan 2022
A Proximal Algorithm for Sampling from Non-smooth Potentials Jiaming Liang Yongxin Chen 108 26 0 09 Oct 2021
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling Keru Wu S. Schmidler Yuansi Chen 127 54 0 27 Sep 2021
Convergence of position-dependent MALA with application to conditional simulation in GLMMs Vivekananda Roy Lijin Zhang 74 8 0 28 Aug 2021
An Introduction to Hamiltonian Monte Carlo Method for Sampling Nisheeth K. Vishnoi 73 14 0 27 Aug 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 88 21 0 02 Aug 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions Y. Lee Ruoqi Shen Kevin Tian 54 20 0 10 Jun 2021
On Irreversible Metropolis Sampling Related to Langevin Dynamics Zexi Song Z. Tan 36 2 0 06 Jun 2021
Mixing Time Guarantees for Unadjusted Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle 110 31 0 03 May 2021
Truncated Log-concave Sampling with Reflective Hamiltonian Monte Carlo Apostolos Chalkis Vissarion Fisikopoulos Marios Papachristou Elias P. Tsigaridas 75 8 0 25 Feb 2021
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm Sinho Chewi Chen Lu Kwangjun Ahn Xiang Cheng Thibaut Le Gouic Philippe Rigollet 105 66 0 23 Dec 2020
Complexity of zigzag sampling algorithm for strongly log-concave distributions Jianfeng Lu Lihan Wang 68 6 0 21 Dec 2020
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 108 36 0 19 Oct 2020
Structured Logconcave Sampling with a Restricted Gaussian Oracle Y. Lee Ruoqi Shen Kevin Tian 82 73 0 07 Oct 2020
Generalized Score Matching for General Domains Shiqing Yu Mathias Drton Ali Shojaie 45 19 0 24 Sep 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 100 49 0 24 Aug 2020
High-dimensional MCMC with a standard splitting scheme for the underdamped Langevin diffusion Pierre Monmarché 102 47 0 10 Jul 2020
Composite Logconcave Sampling with a Restricted Gaussian Oracle Ruoqi Shen Kevin Tian Y. Lee 66 10 0 10 Jun 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Y. Lee Ruoqi Shen Kevin Tian 84 37 0 10 Feb 2020
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds Rong Ge Holden Lee Jianfeng Lu 78 22 0 08 Nov 2019
Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo Bao Wang Difan Zou Quanquan Gu Stanley Osher BDL 62 9 0 02 Nov 2019
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm Wenlong Mou Yian Ma Martin J. Wainwright Peter L. Bartlett Michael I. Jordan DiffM 84 85 0 28 Aug 2019
Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets A. Dalalyan Avetik G. Karagulyan L. Riou-Durand 111 39 0 20 Jun 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 100 71 0 19 Jun 2019
Log-concave sampling: Metropolis-Hastings algorithms are fast Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu 108 255 0 08 Jan 2018