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Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices

20 March 2019

Papers citing "Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices"

50 / 189 papers shown

Title
Transport map unadjusted Langevin algorithms: learning and discretizing perturbed samplers Benjamin J. Zhang Youssef M. Marzouk K. Spiliopoulos 81 0 0 14 Feb 2023
Improved Langevin Monte Carlo for stochastic optimization via landscape modification Michael C. H. Choi Youjia Wang 19 1 0 08 Feb 2023
Non-convex sampling for a mixture of locally smooth potentials D. Nguyen 82 0 0 31 Jan 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates Louis Sharrock Christopher Nemeth BDL 85 8 0 26 Jan 2023
Concentration of the Langevin Algorithm's Stationary Distribution Jason M. Altschuler Kunal Talwar 58 11 0 24 Dec 2022
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 96 20 0 25 Nov 2022
Regularized Stein Variational Gradient Flow Ye He Krishnakumar Balasubramanian Bharath K. Sriperumbudur Jianfeng Lu OT 62 12 0 15 Nov 2022
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 75 3 0 09 Nov 2022
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions Hongrui Chen Holden Lee Jianfeng Lu DiffM 89 142 0 03 Nov 2022
Convergence of the Inexact Langevin Algorithm and Score-based Generative Models in KL Divergence Kaylee Yingxi Yang Andre Wibisono 93 12 0 02 Nov 2022
Birth-death dynamics for sampling: Global convergence, approximations and their asymptotics Yulong Lu D. Slepčev Lihan Wang 115 25 0 01 Nov 2022
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 78 4 0 25 Oct 2022
Forget Unlearning: Towards True Data-Deletion in Machine Learning R. Chourasia Neil Shah MU 83 48 0 17 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 96 25 0 16 Oct 2022
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 88 12 0 13 Oct 2022
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants Andrew M. Childs Tongyang Li Jin-Peng Liu Cong Wang Ruizhe Zhang 64 17 0 12 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 113 15 0 05 Oct 2022
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints Virat Shejwalkar Arun Ganesh Rajiv Mathews Om Thakkar Abhradeep Thakurta 101 8 0 04 Oct 2022
Statistical Efficiency of Score Matching: The View from Isoperimetry Frederic Koehler Alexander Heckett Andrej Risteski DiffM 153 52 0 03 Oct 2022
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences Mikolaj Kasprzak Ryan Giordano Tamara Broderick 66 4 0 29 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 227 278 0 22 Sep 2022
Nesterov smoothing for sampling without smoothness JiaoJiao Fan Bo Yuan Jiaming Liang Yongxin Chen 89 2 0 15 Aug 2022
Bregman Proximal Langevin Monte Carlo via Bregman--Moreau Envelopes Tim Tsz-Kit Lau Han Liu 127 7 0 10 Jul 2022
Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting Ariel Neufeld Matthew Ng Cheng En Ying Zhang 81 12 0 06 Jul 2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time Jun-Kun Wang Andre Wibisono 97 9 0 05 Jul 2022
Langevin Monte Carlo for Contextual Bandits Pan Xu Hongkai Zheng Eric Mazumdar Kamyar Azizzadenesheli Anima Anandkumar 85 28 0 22 Jun 2022
Convergence for score-based generative modeling with polynomial complexity Holden Lee Jianfeng Lu Yixin Tan DiffM 80 140 0 13 Jun 2022
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms Aniket Das Dheeraj M. Nagaraj Anant Raj 106 6 0 08 Jun 2022
Federated Learning with a Sampling Algorithm under Isoperimetry Lukang Sun Adil Salim Peter Richtárik FedML 92 7 0 02 Jun 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 86 19 0 01 Jun 2022
Variational inference via Wasserstein gradient flows Marc Lambert Sinho Chewi Francis R. Bach Silvère Bonnabel Philippe Rigollet BDL DRL 98 77 0 31 May 2022
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods Shunta Akiyama Taiji Suzuki 57 6 0 30 May 2022
Constrained Langevin Algorithms with L-mixing External Random Variables Yu Zheng Andrew G. Lamperski 78 6 0 27 May 2022
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss Jason M. Altschuler Kunal Talwar FedML 139 61 0 27 May 2022
A Proximal Algorithm for Sampling from Non-convex Potentials Jiaming Liang Yongxin Chen 121 4 0 20 May 2022
Convergence of the Riemannian Langevin Algorithm Khashayar Gatmiry Santosh Vempala 67 21 0 22 Apr 2022
Differentially Private Sampling from Rashomon Sets, and the Universality of Langevin Diffusion for Convex Optimization Arun Ganesh Abhradeep Thakurta Jalaj Upadhyay 65 1 0 04 Apr 2022
Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization Yuri Kinoshita Taiji Suzuki 84 17 0 30 Mar 2022
Convergence Error Analysis of Reflected Gradient Langevin Dynamics for Globally Optimizing Non-Convex Constrained Problems Kanji Sato Akiko Takeda Reiichiro Kawai Taiji Suzuki 57 6 0 19 Mar 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) Jiayuan Ye Reza Shokri FedML 95 47 0 10 Mar 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 102 18 0 28 Feb 2022
A Distributed Algorithm for Measure-valued Optimization with Additive Objective Iman Nodozi A. Halder 60 1 0 17 Feb 2022
Improved analysis for a proximal algorithm for sampling Yongxin Chen Sinho Chewi Adil Salim Andre Wibisono 105 58 0 13 Feb 2022
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo Krishnakumar Balasubramanian Sinho Chewi Murat A. Erdogdu Adil Salim Matthew Shunshi Zhang 105 65 0 10 Feb 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 82 12 0 02 Feb 2022
Convex Analysis of the Mean Field Langevin Dynamics Atsushi Nitanda Denny Wu Taiji Suzuki MLT 154 66 0 25 Jan 2022
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 83 5 0 20 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Zohar Ringel 93 55 0 31 Dec 2021
Unadjusted Langevin algorithm for sampling a mixture of weakly smooth potentials D. Nguyen 58 5 0 17 Dec 2021
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees Oren Mangoubi Nisheeth K. Vishnoi 83 15 0 07 Nov 2021