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Log-concave sampling: Metropolis-Hastings algorithms are fast

Log-concave sampling: Metropolis-Hastings algorithms are fast

8 January 2018
Raaz Dwivedi
Yuansi Chen
Martin J. Wainwright
Bin Yu
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Papers citing "Log-concave sampling: Metropolis-Hastings algorithms are fast"

14 / 64 papers shown
Title
Wasserstein Control of Mirror Langevin Monte Carlo
Wasserstein Control of Mirror Langevin Monte Carlo
Kelvin Shuangjian Zhang
Gabriel Peyré
M. Fadili
Marcelo Pereyra
16
65
0
11 Feb 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized
  Hamiltonian Monte Carlo
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
Y. Lee
Ruoqi Shen
Kevin Tian
22
37
0
10 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling
The reproducing Stein kernel approach for post-hoc corrected sampling
Liam Hodgkinson
R. Salomone
Fred Roosta
32
27
0
25 Jan 2020
Aggregated Gradient Langevin Dynamics
Aggregated Gradient Langevin Dynamics
Chao Zhang
Jiahao Xie
Zebang Shen
P. Zhao
Tengfei Zhou
Hui Qian
20
1
0
21 Oct 2019
Estimating Convergence of Markov chains with L-Lag Couplings
Estimating Convergence of Markov chains with L-Lag Couplings
N. Biswas
Pierre E. Jacob
Paul Vanetti
22
47
0
23 May 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using
  ADMM-type Splitting
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting
Maxime Vono
Daniel Paulin
Arnaud Doucet
13
37
0
23 May 2019
On sampling from a log-concave density using kinetic Langevin diffusions
On sampling from a log-concave density using kinetic Langevin diffusions
A. Dalalyan
L. Riou-Durand
21
155
0
24 Jul 2018
Coupling and Convergence for Hamiltonian Monte Carlo
Coupling and Convergence for Hamiltonian Monte Carlo
Nawaf Bou-Rabee
A. Eberle
Raphael Zimmer
77
136
0
01 May 2018
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Oren Mangoubi
Nisheeth K. Vishnoi
25
53
0
24 Feb 2018
Sampling as optimization in the space of measures: The Langevin dynamics
  as a composite optimization problem
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem
Andre Wibisono
21
177
0
22 Feb 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal
  Distributions using Simulated Tempering Langevin Monte Carlo
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo
Rong Ge
Holden Lee
Andrej Risteski
23
53
0
07 Oct 2017
Complexity Results for MCMC derived from Quantitative Bounds
Complexity Results for MCMC derived from Quantitative Bounds
Jun Yang
Jeffrey S. Rosenthal
29
23
0
02 Aug 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex
  Optimization
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
Pan Xu
Jinghui Chen
Difan Zou
Quanquan Gu
31
200
0
20 Jul 2017
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
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