Log-concave sampling: Metropolis-Hastings algorithms are fast

8 January 2018

Papers citing "Log-concave sampling: Metropolis-Hastings algorithms are fast"

50 / 61 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
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 107 0 0 11 Apr 2025
On the query complexity of sampling from non-log-concave distributions Yuchen He Chihao Zhang 41 0 0 10 Feb 2025
Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality Andre Wibisono 53 1 0 08 Feb 2025
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance Marta Gentiloni-Silveri Antonio Ocello 37 2 0 04 Jan 2025
Score-Based Metropolis-Hastings Algorithms Ahmed Aloui Ali Hasan Juncheng Dong Zihao Wu Vahid Tarokh DiffM 34 0 0 31 Dec 2024
Spectral gap bounds for reversible hybrid Gibbs chains Qian Qin Nianqiao Ju Guanyang Wang 31 5 0 20 Dec 2023
Quantum Langevin Dynamics for Optimization Zherui Chen Yuchen Lu Hao Wang Yizhou Liu Tongyang Li AI4CE 21 9 0 27 Nov 2023
Accelerating optimization over the space of probability measures Shi Chen Wenxuan Wu Yuhang Yao Stephen J. Wright 26 4 0 06 Oct 2023
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators B. Leimkuhler Daniel Paulin P. Whalley 23 5 0 14 Jun 2023
Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen Yuheng Bu Greg Wornell 21 1 0 08 Jun 2023
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? Yuansi Chen Khashayar Gatmiry 94 15 0 10 Apr 2023
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry Yuansi Chen Khashayar Gatmiry 11 6 0 08 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
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 26 6 0 08 Mar 2023
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation David Holzmüller Francis R. Bach 29 8 0 06 Mar 2023
Efficiently handling constraints with Metropolis-adjusted Langevin algorithm Jinyuan Chang C. Tang Yuanzheng Zhu 16 1 0 23 Feb 2023
Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics B. Leimkuhler Daniel Paulin P. Whalley 32 16 0 21 Feb 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
Fast Replica Exchange Stochastic Gradient Langevin Dynamics Guanxun Li Guang Lin Zecheng Zhang Quan Zhou 123 4 0 05 Jan 2023
Improving multiple-try Metropolis with local balancing Philippe Gagnon Florian Maire Giacomo Zanella 31 9 0 21 Nov 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 27 24 0 16 Oct 2022
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 35 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 20 16 0 12 Oct 2022
Denoising MCMC for Accelerating Diffusion-Based Generative Models Beomsu Kim Jong Chul Ye DiffM 49 13 0 29 Sep 2022
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps Simon Apers S. Gribling Dániel Szilágyi 28 10 0 26 Sep 2022
Nesterov smoothing for sampling without smoothness JiaoJiao Fan Bo Yuan Jiaming Liang Yongxin Chen 37 2 0 15 Aug 2022
Enhanced gradient-based MCMC in discrete spaces Benjamin Rhodes Michael U. Gutmann 26 15 0 29 Jul 2022
Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk Oren Mangoubi Nisheeth K. Vishnoi 69 2 0 19 Jun 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 21 19 0 01 Jun 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo L. Riou-Durand Jure Vogrinc 18 14 0 26 Feb 2022
Order-based Structure Learning without Score Equivalence Hyunwoong Chang James Cai Quan Zhou CML OffRL 21 3 0 10 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
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 20 10 0 02 Feb 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications Se Yoon Lee 17 17 0 28 Jan 2022
Metropolis Augmented Hamiltonian Monte Carlo Guangyao Zhou 33 1 0 20 Jan 2022
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 17 8 0 06 Dec 2021
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees Oren Mangoubi Nisheeth K. Vishnoi 14 14 0 07 Nov 2021
A Proximal Algorithm for Sampling from Non-smooth Potentials Jiaming Liang Yongxin Chen 31 26 0 09 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 32 16 0 05 Oct 2021
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley BDL AI4CE 24 8 0 26 Jul 2021
Scalable Bayesian computation for crossed and nested hierarchical models O. Papaspiliopoulos Timothée Stumpf-Fétizon Giacomo Zanella 37 10 0 19 Mar 2021
Data-Free Likelihood-Informed Dimension Reduction of Bayesian Inverse Problems Tiangang Cui O. Zahm 17 22 0 26 Feb 2021
On the cost of Bayesian posterior mean strategy for log-concave models S. Gadat Fabien Panloup Clément Pellegrini 18 7 0 08 Oct 2020
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors Yuling Yao Aki Vehtari Andrew Gelman 29 60 0 22 Jun 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 32 50 0 14 Jun 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence Sinho Chewi Thibaut Le Gouic Chen Lu Tyler Maunu Philippe Rigollet 31 66 0 03 Jun 2020
On the limitations of single-step drift and minorization in Markov chain convergence analysis Qian Qin J. Hobert 12 29 0 21 Mar 2020
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang Gabriel Peyré M. Fadili Marcelo Pereyra 13 65 0 11 Feb 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Y. Lee Ruoqi Shen Kevin Tian 17 37 0 10 Feb 2020