Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions

10 June 2021

Papers citing "Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions"

11 / 11 papers shown

Title
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? Yuansi Chen Khashayar Gatmiry 99 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
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 35 24 0 16 Oct 2022
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants Andrew M. Childs Tongyang Li Jin-Peng Liu Cong Wang Ruizhe Zhang 34 16 0 12 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 49 15 0 05 Oct 2022
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps Simon Apers S. Gribling Dániel Szilágyi 36 10 0 26 Sep 2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time Jun-Kun Wang Andre Wibisono 27 9 0 05 Jul 2022
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 24 19 0 02 Aug 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 31 21 0 29 May 2021
Mixing Time Guarantees for Unadjusted Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle 58 29 0 03 May 2021