Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation

28 June 2019

Papers citing "Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation"

21 / 21 papers shown

Title
Proximal Interacting Particle Langevin Algorithms Paula Cordero Encinar F. R. Crucinio O. Deniz Akyildiz 61 5 0 20 Jun 2024
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 70 13 0 23 Mar 2023
Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part II: Theoretical Analysis Valentin De Bortoli Alain Durmus A. F. Vidal Marcelo Pereyra 52 20 0 13 Aug 2020
Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part I: Methodology and Experiments A. F. Vidal Valentin De Bortoli Marcelo Pereyra Alain Durmus 59 7 0 26 Nov 2019
A Dynamical Systems Perspective on Nesterov Acceleration Michael Muehlebach Michael I. Jordan 51 120 0 17 May 2019
Convergence of diffusions and their discretizations: from continuous to discrete processes and back Valentin De Bortoli Alain Durmus 22 21 0 22 Apr 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 49 78 0 04 Feb 2019
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme Belhal Karimi B. Miasojedow Eric Moulines Hoi-To Wai 42 90 0 02 Feb 2019
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 63 154 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 45 166 0 04 May 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo Rong Ge Holden Lee Andrej Risteski 64 54 0 07 Oct 2017
On the convergence of Hamiltonian Monte Carlo Alain Durmus Eric Moulines E. Saksman 63 70 0 29 Apr 2017
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent A. Dalalyan BDL 40 174 0 16 Apr 2017
Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau Alain Durmus Eric Moulines Marcelo Pereyra 51 176 0 22 Dec 2016
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 61 410 0 17 Jul 2015
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 66 514 0 23 Dec 2014
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 58 231 0 01 Sep 2014
On perturbed proximal gradient algorithms Yves Atchadé G. Fort Eric Moulines 59 99 0 11 Feb 2014
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 72 305 0 27 Jun 2012
Convergence of adaptive and interacting Markov chain Monte Carlo algorithms G. Fort Eric Moulines P. Priouret 54 100 0 14 Mar 2012
Computational methods for Bayesian model choice Christian P. Robert Darren Wraith 86 74 0 29 Jul 2009