v1v2v3 (latest)

A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics

19 July 2022

Papers citing "A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics"

24 / 24 papers shown

Title
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 432 1 0 08 Oct 2024
Geometric ergodicity of SGLD via reflection coupling Lei Li Jian‐Guo Liu Yuliang Wang 87 2 0 17 Jan 2023
On uniform-in-time diffusion approximation for stochastic gradient descent Lei Li Yuliang Wang 83 4 0 11 Jul 2022
Time-independent Generalization Bounds for SGLD in Non-convex Settings Tyler Farghly Patrick Rebeschini 81 24 0 25 Nov 2021
SGD with a Constant Large Learning Rate Can Converge to Local Maxima Liu Ziyin Botao Li James B. Simon Masakuni Ueda 50 9 0 25 Jul 2021
On the Origin of Implicit Regularization in Stochastic Gradient Descent Samuel L. Smith Benoit Dherin David Barrett Soham De MLT 47 204 0 28 Jan 2021
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 86 36 0 19 Oct 2020
On the Generalization Benefit of Noise in Stochastic Gradient Descent Samuel L. Smith Erich Elsen Soham De MLT 55 100 0 26 Jun 2020
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization Ying Zhang Ömer Deniz Akyildiz Theodoros Damoulas Sotirios Sabanis 76 47 0 04 Oct 2019
Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity Wenlong Mou Nicolas Flammarion Martin J. Wainwright Peter L. Bartlett 52 68 0 25 Jul 2019
Uniform-in-Time Weak Error Analysis for Stochastic Gradient Descent Algorithms via Diffusion Approximation Yuanyuan Feng Tingran Gao Lei Li Jian‐Guo Liu Yulong Lu 45 25 0 02 Feb 2019
The promises and pitfalls of Stochastic Gradient Langevin Dynamics N. Brosse Alain Durmus Eric Moulines 67 78 0 25 Nov 2018
Non-asymptotic bounds for sampling algorithms without log-concavity Mateusz B. Majka Aleksandar Mijatović Lukasz Szpruch 48 73 0 21 Aug 2018
An Alternative View: When Does SGD Escape Local Minima? Robert D. Kleinberg Yuanzhi Li Yang Yuan MLT 77 317 0 17 Feb 2018
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 75 297 0 29 Sep 2017
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints Wenlong Mou Liwei Wang Xiyu Zhai Kai Zheng MLT 57 159 0 19 Jul 2017
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics Yuchen Zhang Percy Liang Moses Charikar 69 236 0 18 Feb 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 75 521 0 13 Feb 2017
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan Luke Vilnis Quoc V. Le Ilya Sutskever Lukasz Kaiser Karol Kurach James Martens AI4CE ODL 83 545 0 21 Nov 2015
Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li Sungjin Ahn Max Welling BDL 82 42 0 16 Oct 2015
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 86 516 0 23 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,312 0 22 Dec 2014
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 85 235 0 01 Sep 2014
Sparse Regression Learning by Aggregation and Langevin Monte-Carlo A. Dalalyan Alexandre B. Tsybakov 185 180 0 06 Mar 2009