The promises and pitfalls of Stochastic Gradient Langevin Dynamics

25 November 2018

Papers citing "The promises and pitfalls of Stochastic Gradient Langevin Dynamics"

22 / 22 papers shown

Title
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 135 3 0 28 Jan 2025
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning S. Samsonov Eric Moulines Qi-Man Shao Zhuo-Song Zhang Alexey Naumov 68 5 0 26 May 2024
3D Gaussian Splatting as Markov Chain Monte Carlo Shakiba Kheradmand Daniel Rebain Gopal Sharma Weiwei Sun Jeff Tseng Hossam N. Isack Abhishek Kar Andrea Tagliasacchi Kwang Moo Yi 3DGS 76 52 0 15 Apr 2024
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo Niladri S. Chatterji Nicolas Flammarion Yian Ma Peter L. Bartlett Michael I. Jordan 56 87 0 15 Feb 2018
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 62 296 0 29 Sep 2017
A Convergence Analysis for A Class of Practical Variance-Reduction Stochastic Gradient MCMC Changyou Chen Wenlin Wang Yizhe Zhang Qinliang Su Lawrence Carin 57 28 0 04 Sep 2017
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains Aymeric Dieuleveut Alain Durmus Francis R. Bach 31 154 0 20 Jul 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 49 101 0 16 Jun 2017
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent A. Dalalyan BDL 42 174 0 16 Apr 2017
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 60 159 0 21 Oct 2016
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 74 352 0 05 May 2016
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server Leonard Hasenclever Stefan Webb Thibaut Lienart Sebastian J. Vollmer Balaji Lakshminarayanan Charles Blundell Yee Whye Teh BDL 102 70 0 31 Dec 2015
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 76 325 0 23 Dec 2015
Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li Sungjin Ahn Max Welling BDL 61 42 0 16 Oct 2015
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 61 410 0 17 Jul 2015
A Complete Recipe for Stochastic Gradient MCMC Yian Ma Tianqi Chen E. Fox BDL SyDa 60 485 0 15 Jun 2015
On Markov chain Monte Carlo methods for tall data Rémi Bardenet Arnaud Doucet Chris Holmes 71 276 0 11 May 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
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 93 906 0 17 Feb 2014
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget Anoop Korattikara Yutian Chen Max Welling 68 243 0 19 Apr 2013
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 74 305 0 27 Jun 2012