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High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm

5 May 2016

Papers citing "High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm"

45 / 145 papers shown

Title
Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity Wenlong Mou Nicolas Flammarion Martin J. Wainwright Peter L. Bartlett 68 68 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 111 39 0 20 Jun 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 96 71 0 19 Jun 2019
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 105 43 0 30 May 2019
On stochastic gradient Langevin dynamics with dependent data streams: the fully non-convex case N. H. Chau '. Moulines Miklós Rásonyi Sotirios Sabanis Ying Zhang 83 41 0 30 May 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 132 37 0 23 May 2019
Convergence of diffusions and their discretizations: from continuous to discrete processes and back Valentin De Bortoli Alain Durmus 60 22 0 22 Apr 2019
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 71 10 0 25 Mar 2019
TATi-Thermodynamic Analytics ToolkIt: TensorFlow-based software for posterior sampling in machine learning applications Frederik Heber Zofia Trstanova Benedict Leimkuhler 26 1 0 20 Mar 2019
Asymptotically exact data augmentation: models, properties and algorithms Maxime Vono N. Dobigeon P. Chainais 66 27 0 15 Feb 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 85 78 0 04 Feb 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space Chang-Shu Liu Jingwei Zhuo Jun Zhu 106 22 0 01 Feb 2019
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization T. H. Nguyen Umut Simsekli G. Richard 80 28 0 22 Jan 2019
Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities Y. Lee Zhao Song Santosh Vempala 93 37 0 15 Dec 2018
On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case M. Barkhagen N. H. Chau '. Moulines Miklós Rásonyi S. Sabanis Ying Zhang 92 38 0 06 Dec 2018
Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition Rong Ge Holden Lee Andrej Risteski 185 29 0 29 Nov 2018
The promises and pitfalls of Stochastic Gradient Langevin Dynamics N. Brosse Alain Durmus Eric Moulines 88 78 0 25 Nov 2018
Sampling Can Be Faster Than Optimization Yian Ma Yuansi Chen Chi Jin Nicolas Flammarion Michael I. Jordan 72 186 0 20 Nov 2018
Non-Asymptotic Guarantees For Sampling by Stochastic Gradient Descent Avetik G. Karagulyan 21 1 0 02 Nov 2018
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 62 28 0 25 Sep 2018
Non-asymptotic bounds for sampling algorithms without log-concavity Mateusz B. Majka Aleksandar Mijatović Lukasz Szpruch 67 75 0 21 Aug 2018
Higher Order Langevin Monte Carlo Algorithm Sotirios Sabanis Ying Zhang 82 23 0 02 Aug 2018
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 120 158 0 24 Jul 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 82 167 0 04 May 2018
Mirrored Langevin Dynamics Ya-Ping Hsieh Ali Kavis Paul Rolland Volkan Cevher 102 85 0 27 Feb 2018
Analysis of Langevin Monte Carlo via convex optimization Alain Durmus Szymon Majewski B. Miasojedow 108 222 0 26 Feb 2018
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo Oren Mangoubi Nisheeth K. Vishnoi 155 53 0 24 Feb 2018
Langevin Monte Carlo and JKO splitting Espen Bernton 88 80 0 23 Feb 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 123 183 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 86 87 0 15 Feb 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 72 31 0 13 Feb 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu 99 255 0 08 Jan 2018
Convergence complexity analysis of Albert and Chib's algorithm for Bayesian probit regression Qian Qin J. Hobert 63 32 0 24 Dec 2017
Natural Langevin Dynamics for Neural Networks Gaétan Marceau-Caron Yann Ollivier BDL 77 30 0 04 Dec 2017
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo Rong Ge Holden Lee Andrej Risteski 96 53 0 07 Oct 2017
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 99 297 0 29 Sep 2017
Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions Oren Mangoubi Aaron Smith 136 106 0 23 Aug 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization Pan Xu Jinghui Chen Difan Zou Quanquan Gu 90 205 0 20 Jul 2017
Underdamped Langevin MCMC: A non-asymptotic analysis Xiang Cheng Niladri S. Chatterji Peter L. Bartlett Michael I. Jordan 146 302 0 12 Jul 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 91 101 0 16 Jun 2017
Convergence of Langevin MCMC in KL-divergence Xiang Cheng Peter L. Bartlett 78 194 0 25 May 2017
Bayes Shrinkage at GWAS scale: Convergence and Approximation Theory of a Scalable MCMC Algorithm for the Horseshoe Prior J. Johndrow Paulo Orenstein A. Bhattacharya 90 24 0 02 May 2017
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent A. Dalalyan BDL 52 175 0 16 Apr 2017
Rapid Mixing of Geodesic Walks on Manifolds with Positive Curvature Oren Mangoubi Aaron Smith OT 101 22 0 09 Sep 2016
Ensemble preconditioning for Markov chain Monte Carlo simulation Charles Matthews Jonathan Weare Benedict Leimkuhler 67 57 0 13 Jul 2016