Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities

15 December 2018

Papers citing "Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities"

8 / 8 papers shown

Title
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration Nawaf Bou-Rabee Milo Marsden 32 12 0 20 Nov 2022
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi Ma Tong Zhang 37 16 0 05 Oct 2021
Complexity of zigzag sampling algorithm for strongly log-concave distributions Jianfeng Lu Lihan Wang 18 6 0 21 Dec 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Y. Lee Ruoqi Shen Kevin Tian 25 37 0 10 Feb 2020
Efficient Symmetric Norm Regression via Linear Sketching Zhao Song Ruosong Wang Lin F. Yang Hongyang R. Zhang Peilin Zhong 20 22 0 04 Oct 2019
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 13 43 0 30 May 2019
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions Zongchen Chen Santosh Vempala 11 64 0 07 May 2019
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 58 231 0 11 Jul 2016