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User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient

29 September 2017

Papers citing "User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient"

50 / 133 papers shown

Title
Decentralized Langevin Dynamics over a Directed Graph Alexander Kolesov Vyacheslav Kungurtsev 63 2 0 06 Mar 2021
Stochastic Gradient Langevin Dynamics with Variance Reduction Zhishen Huang Stephen Becker 82 7 0 12 Feb 2021
Higher Order Generalization Error for First Order Discretization of Langevin Diffusion Mufan Li Maxime Gazeau 33 1 0 11 Feb 2021
Unadjusted Langevin algorithm for non-convex weakly smooth potentials D. Nguyen Xin Dang Yixin Chen 78 14 0 16 Jan 2021
A fresh take on 'Barker dynamics' for MCMC Max Hird Samuel Livingstone Giacomo Zanella 93 9 0 17 Dec 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 66 35 0 06 Nov 2020
Random Coordinate Underdamped Langevin Monte Carlo Zhiyan Ding Qin Li Jianfeng Lu Stephen J. Wright BDL 93 13 0 22 Oct 2020
Riemannian Langevin Algorithm for Solving Semidefinite Programs Mufan Li Murat A. Erdogdu 118 29 0 21 Oct 2020
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 108 36 0 19 Oct 2020
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev Tianlin Li Qi Lei Ioannis Panageas 65 20 0 11 Oct 2020
Structured Logconcave Sampling with a Restricted Gaussian Oracle Y. Lee Ruoqi Shen Kevin Tian 82 73 0 07 Oct 2020
Variance reduction for dependent sequences with applications to Stochastic Gradient MCMC Denis Belomestny L. Iosipoi Eric Moulines A. Naumov S. Samsonov 72 6 0 16 Aug 2020
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 83 20 0 13 Aug 2020
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms A. Lovas Iosif Lytras Miklós Rásonyi Sotirios Sabanis 88 26 0 25 Jun 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent Anna Korba Adil Salim Michael Arbel Giulia Luise Arthur Gretton 84 78 0 17 Jun 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 106 52 0 14 Jun 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 88 77 0 27 May 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC Ruqi Zhang A. Feder Cooper Christopher De Sa 88 18 0 29 Feb 2020
On Thompson Sampling with Langevin Algorithms Eric Mazumdar Aldo Pacchiano Yi-An Ma Peter L. Bartlett Michael I. Jordan 67 11 0 23 Feb 2020
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients Ruilin Li Xin Wang H. Zha Molei Tao 34 4 0 20 Feb 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 97 17 0 13 Feb 2020
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang Gabriel Peyré M. Fadili Marcelo Pereyra 71 66 0 11 Feb 2020
Oracle Lower Bounds for Stochastic Gradient Sampling Algorithms Niladri S. Chatterji Peter L. Bartlett Philip M. Long 63 8 0 01 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 72 27 0 25 Jan 2020
Replica Exchange for Non-Convex Optimization Jing-rong Dong Xin T. Tong 108 21 0 23 Jan 2020
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation N. Brosse C. Riquelme Alice Martin Sylvain Gelly Eric Moulines BDL OOD UQCV 97 34 0 22 Jan 2020
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds Rong Ge Holden Lee Jianfeng Lu 78 22 0 08 Nov 2019
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 144 49 0 04 Nov 2019
Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo Bao Wang Difan Zou Quanquan Gu Stanley Osher BDL 62 9 0 02 Nov 2019
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 126 44 0 23 Oct 2019
Aggregated Gradient Langevin Dynamics Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 81 1 0 21 Oct 2019
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization Ying Zhang Ömer Deniz Akyildiz Theodoros Damoulas Sotirios Sabanis 106 47 0 04 Oct 2019
The Randomized Midpoint Method for Log-Concave Sampling Ruoqi Shen Y. Lee 125 118 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 84 85 0 28 Aug 2019
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
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 83 139 0 16 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 100 71 0 19 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim Arthur Gretton 132 164 0 11 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 97 41 0 30 May 2019
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients Yuansi Chen Raaz Dwivedi Martin J. Wainwright Bin Yu 55 102 0 29 May 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates Adil Salim D. Kovalev Peter Richtárik 85 26 0 28 May 2019
Estimating Convergence of Markov chains with L-Lag Couplings N. Biswas Pierre E. Jacob Paul Vanetti 58 49 0 23 May 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 134 37 0 23 May 2019
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions Zongchen Chen Santosh Vempala 84 65 0 07 May 2019
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics Xi Chen S. Du Xin T. Tong 79 33 0 30 Apr 2019
Optimal Scaling of Random-Walk Metropolis Algorithms on General Target Distributions Jun Yang Gareth O. Roberts Jeffrey S. Rosenthal OT 95 29 0 27 Apr 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