Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting

23 May 2019

Papers citing "Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting"

25 / 25 papers shown

Title
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 119 1 0 08 Oct 2024
A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design Atlanta Chakraborty Xun Huan Tommie A. Catanach 29 3 0 18 Aug 2024
Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference Conor Hassan Matthew Sutton Antonietta Mira Kerrie Mengersen FedML 23 1 0 07 May 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction Xingyu Xu Yuejie Chi DiffM 42 20 0 25 Mar 2024
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers Alexandros E. Tzikas Licio Romao Mert Pilanci Alessandro Abate Mykel J. Kochenderfer 26 0 0 29 Jan 2024
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples Leo L. Duan Anirban Bhattacharya 8 1 0 25 Jan 2024
Reflected Schrödinger Bridge for Constrained Generative Modeling Wei Deng Yu Chen Nicole Tianjiao Yang Hengrong Du Qi Feng Ricky T. Q. Chen 29 7 0 06 Jan 2024
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling Teresa Klatzer P. Dobson Y. Altmann Marcelo Pereyra J. Sanz-Serna K. Zygalakis 11 5 0 18 Aug 2023
Subgradient Langevin Methods for Sampling from Non-smooth Potentials Andreas Habring M. Holler T. Pock 16 8 0 02 Aug 2023
On a Class of Gibbs Sampling over Networks Bo Yuan JiaoJiao Fan Jiaming Liang Andre Wibisono Yongxin Chen 49 6 0 23 Jun 2023
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms Tim Tsz-Kit Lau Han Liu T. Pock 39 4 0 25 May 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 33 4 0 21 Apr 2023
Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference Florentin Coeurdoux N. Dobigeon P. Chainais 25 14 0 21 Apr 2023
Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling Ye He Tyler Farghly Krishnakumar Balasubramanian Murat A. Erdogdu 36 4 0 01 Mar 2023
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms Vincent Plassier Alain Durmus Eric Moulines FedML 14 6 0 31 Oct 2022
Approximate blocked Gibbs sampling for Bayesian neural networks Theodore Papamarkou BDL 132 2 0 24 Aug 2022
The split Gibbs sampler revisited: improvements to its algorithmic structure and augmented target distribution Marcelo Pereyra L. Mieles K. Zygalakis 34 6 0 28 Jun 2022
Improved analysis for a proximal algorithm for sampling Yongxin Chen Sinho Chewi Adil Salim Andre Wibisono 11 54 0 13 Feb 2022
A Proximal Algorithm for Sampling from Non-smooth Potentials Jiaming Liang Yongxin Chen 31 26 0 09 Oct 2021
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs Vincent Plassier Maxime Vono Alain Durmus Eric Moulines 6 17 0 11 Jun 2021
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning Maxime Vono Vincent Plassier Alain Durmus Aymeric Dieuleveut Eric Moulines FedML 22 35 0 01 Jun 2021
High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm Maxime Vono N. Dobigeon P. Chainais 8 31 0 04 Oct 2020
Randomized Hamiltonian Monte Carlo as Scaling Limit of the Bouncy Particle Sampler and Dimension-Free Convergence Rates George Deligiannidis Daniel Paulin Alexandre Bouchard-Coté Arnaud Doucet 8 51 0 13 Aug 2018
Global consensus Monte Carlo Lewis J. Rendell A. M. Johansen Anthony Lee N. Whiteley 11 39 0 24 Jul 2018
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 58 232 0 11 Jul 2016