On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness

27 May 2020

Papers citing "On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness"

41 / 41 papers shown

Title
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 50 33 0 06 Nov 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 87 51 0 14 Jun 2020
Black-box sampling for weakly smooth Langevin Monte Carlo using p-generalized Gaussian smoothing Anh Doan Xin Dang D. Nguyen 18 1 0 24 Feb 2020
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds Rong Ge Holden Lee Jianfeng Lu 43 22 0 08 Nov 2019
An Efficient Sampling Algorithm for Non-smooth Composite Potentials Wenlong Mou Nicolas Flammarion Martin J. Wainwright Peter L. Bartlett 35 24 0 01 Oct 2019
The Randomized Midpoint Method for Log-Concave Sampling Ruoqi Shen Y. Lee 89 115 0 12 Sep 2019
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm Wenlong Mou Yian Ma Martin J. Wainwright Peter L. Bartlett Michael I. Jordan DiffM 43 85 0 28 Aug 2019
Bayesian Robustness: A Nonasymptotic Viewpoint Kush S. Bhatia Yian Ma Anca Dragan Peter L. Bartlett Michael I. Jordan 26 7 0 27 Jul 2019
Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity Wenlong Mou Nicolas Flammarion Martin J. Wainwright Peter L. Bartlett 34 67 0 25 Jul 2019
Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets A. Dalalyan Avetik G. Karagulyan L. Riou-Durand 51 38 0 20 Jun 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 36 71 0 19 Jun 2019
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 72 43 0 30 May 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices Santosh Vempala Andre Wibisono 79 264 0 20 Mar 2019
Is There an Analog of Nesterov Acceleration for MCMC? Yian Ma Niladri Chatterji Xiang Cheng Nicolas Flammarion Peter L. Bartlett Michael I. Jordan BDL 54 78 0 04 Feb 2019
Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition Rong Ge Holden Lee Andrej Risteski 117 28 0 29 Nov 2018
The promises and pitfalls of Stochastic Gradient Langevin Dynamics N. Brosse Alain Durmus Eric Moulines 55 78 0 25 Nov 2018
Sampling Can Be Faster Than Optimization Yian Ma Yuansi Chen Chi Jin Nicolas Flammarion Michael I. Jordan 65 184 0 20 Nov 2018
Global Non-convex Optimization with Discretized Diffusions Murat A. Erdogdu Lester W. Mackey Ohad Shamir 66 105 0 29 Oct 2018
Non-asymptotic bounds for sampling algorithms without log-concavity Mateusz B. Majka Aleksandar Mijatović Lukasz Szpruch 46 73 0 21 Aug 2018
Sharp convergence rates for Langevin dynamics in the nonconvex setting Xiang Cheng Niladri S. Chatterji Yasin Abbasi-Yadkori Peter L. Bartlett Michael I. Jordan 47 166 0 04 May 2018
Mirrored Langevin Dynamics Ya-Ping Hsieh Ali Kavis Paul Rolland Volkan Cevher 71 85 0 27 Feb 2018
Analysis of Langevin Monte Carlo via convex optimization Alain Durmus Szymon Majewski B. Miasojedow 62 219 0 26 Feb 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 93 179 0 22 Feb 2018
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo Niladri S. Chatterji Nicolas Flammarion Yian Ma Peter L. Bartlett Michael I. Jordan 60 87 0 15 Feb 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu 66 254 0 08 Jan 2018
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 65 296 0 29 Sep 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization Pan Xu Jinghui Chen Difan Zou Quanquan Gu 68 205 0 20 Jul 2017
Underdamped Langevin MCMC: A non-asymptotic analysis Xiang Cheng Niladri S. Chatterji Peter L. Bartlett Michael I. Jordan 82 297 0 12 Jul 2017
Convergence of Langevin MCMC in KL-divergence Xiang Cheng Peter L. Bartlett 47 190 0 25 May 2017
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent A. Dalalyan BDL 45 174 0 16 Apr 2017
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics Yuchen Zhang Percy Liang Moses Charikar 61 236 0 18 Feb 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 70 521 0 13 Feb 2017
Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau Alain Durmus Eric Moulines Marcelo Pereyra 53 176 0 22 Dec 2016
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 68 116 0 21 Nov 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 252 1,216 0 16 Aug 2016
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 74 33 0 05 May 2016
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 64 412 0 17 Jul 2015
A Complete Recipe for Stochastic Gradient MCMC Yian Ma Tianqi Chen E. Fox BDL SyDa 60 486 0 15 Jun 2015
A Moreau-Yosida approximation scheme for a class of high-dimensional posterior distributions Yves F. Atchadé 57 11 0 26 May 2015
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 66 514 0 23 Dec 2014
Sparse Regression Learning by Aggregation and Langevin Monte-Carlo A. Dalalyan Alexandre B. Tsybakov 164 179 0 06 Mar 2009