Consistency and fluctuations for stochastic gradient Langevin dynamics

1 September 2014

Papers citing "Consistency and fluctuations for stochastic gradient Langevin dynamics"

46 / 46 papers shown

Title
Drift to Remember Jin Du X. Zhang Hao Shen Xun Xian Ganghua Wang Jiawei Zhang Yuhong Yang Na Li Jia Liu Jie Ding CLL 16 0 0 21 Sep 2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics Lorenzo Mauri Giacomo Zanella 27 3 0 14 May 2024
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 26 0 0 05 Mar 2024
Sampling and estimation on manifolds using the Langevin diffusion Karthik Bharath Alexander Lewis Akash Sharma M. Tretyakov DiffM 69 5 0 22 Dec 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 23 20 0 29 May 2023
Fast Replica Exchange Stochastic Gradient Langevin Dynamics Guanxun Li Guang Lin Zecheng Zhang Quan Zhou 117 4 0 05 Jan 2023
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 29 4 0 25 Oct 2022
A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics Lei Li Yuliang Wang 37 11 0 19 Jul 2022
Bayesian Learning of Parameterised Quantum Circuits Samuel Duffield Marcello Benedetti Matthias Rosenkranz 14 11 0 15 Jun 2022
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 19 2 0 26 Mar 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 23 10 0 20 Feb 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao-quan Song Guang Lin FedML 22 16 0 09 Dec 2021
Deep Bayesian inference for seismic imaging with tasks Ali Siahkoohi G. Rizzuti Felix J. Herrmann BDL UQCV 30 21 0 10 Oct 2021
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo Vyacheslav Kungurtsev Adam D. Cobb T. Javidi Brian Jalaian 51 4 0 15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 30 1,109 0 07 Jul 2021
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 34 27 0 19 Oct 2020
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng Qi Feng G. Karagiannis Guang Lin F. Liang 14 8 0 02 Oct 2020
Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen Colin Wei J. Lee Tengyu Ma 18 93 0 15 Jun 2020
Powering One-shot Topological NAS with Stabilized Share-parameter Proxy Ronghao Guo Chen Lin Chuming Li Keyu Tian Ming-hui Sun Lu Sheng Junjie Yan BDL 13 17 0 21 May 2020
Federated Stochastic Gradient Langevin Dynamics Khaoula El Mekkaoui Diego Mesquita P. Blomstedt Samuel Kaski FedML 11 24 0 23 Apr 2020
Estimating Motion Uncertainty with Bayesian ICP F. A. Maken F. Ramos Lionel Ott 3DPC 22 9 0 16 Apr 2020
Aggregated Gradient Langevin Dynamics Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 10 1 0 21 Oct 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 16 135 0 16 Jul 2019
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 13 37 0 06 Dec 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 10 46 0 05 Sep 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 13 86 0 29 May 2018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors Gintare Karolina Dziugaite Daniel M. Roy MLT 20 144 0 26 Dec 2017
On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li Changyou Chen Hao Liu Lawrence Carin 27 38 0 25 Dec 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 13 32 0 26 Sep 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 32 57 0 04 Sep 2017
Hamiltonian Monte Carlo with Energy Conserving Subsampling Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran M. Villani 25 62 0 02 Aug 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 22 101 0 16 Jun 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 45 41 0 23 Nov 2016
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 22 116 0 21 Nov 2016
Multilevel Monte Carlo for Scalable Bayesian Computations M. Giles Tigran Nagapetyan Lukasz Szpruch Sebastian J. Vollmer K. Zygalakis 21 9 0 15 Sep 2016
Merging MCMC Subposteriors through Gaussian-Process Approximations Christopher Nemeth Chris Sherlock 16 49 0 27 May 2016
Coresets for Scalable Bayesian Logistic Regression Jonathan H. Huggins Trevor Campbell Tamara Broderick 11 216 0 20 May 2016
Quantifying the accuracy of approximate diffusions and Markov chains Jonathan H. Huggins James Y. Zou 49 29 0 20 May 2016
Stochastic Quasi-Newton Langevin Monte Carlo Umut Simsekli Roland Badeau A. Cemgil G. Richard BDL 14 59 0 10 Feb 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 22 319 0 23 Dec 2015
The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method Alexandre Bouchard-Coté Sebastian J. Vollmer Arnaud Doucet 21 236 0 08 Oct 2015
Provable Bayesian Inference via Particle Mirror Descent Bo Dai Niao He H. Dai Le Song 28 70 0 09 Jun 2015
Parallel Stochastic Gradient Markov Chain Monte Carlo for Matrix Factorisation Models Umut Simsekli Hazal Koptagel Hakan Güldaş taylan. cemgil Figen Oztoprak Ilker Birbil 23 12 0 03 Jun 2015
Fast Differentially Private Matrix Factorization Ziqi Liu Yu-Xiang Wang Alex Smola FedML 40 124 0 06 May 2015
Perturbation theory for Markov chains via Wasserstein distance Daniel Rudolf Nikolaus Schweizer 40 107 0 13 Mar 2015
Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) Maurizio Filippone Raphael Engler 24 31 0 22 Jan 2015