Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo

10 February 2020

Papers citing "Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo"

10 / 10 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
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? Yuansi Chen Khashayar Gatmiry 94 15 0 10 Apr 2023
Query lower bounds for log-concave sampling Sinho Chewi Jaume de Dios Pont Jerry Li Chen Lu Shyam Narayanan 32 8 0 05 Apr 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler Sivakanth Gopi Y. Lee Daogao Liu Ruoqi Shen Kevin Tian 17 7 0 13 Feb 2023
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 38 12 0 13 Oct 2022
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants Andrew M. Childs Tongyang Li Jin-Peng Liu C. Wang Ruizhe Zhang 25 16 0 12 Oct 2022
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps Simon Apers S. Gribling Dániel Szilágyi 28 10 0 26 Sep 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo L. Riou-Durand Jure Vogrinc 18 14 0 26 Feb 2022
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 11 38 0 03 Feb 2022
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 24 19 0 02 Aug 2021