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Convergence of Langevin MCMC in KL-divergence

25 May 2017

Papers citing "Convergence of Langevin MCMC in KL-divergence"

50 / 73 papers shown

Title
Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality Andre Wibisono 122 1 0 01 Jul 2025
Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures Nina Vesseron Louis Béthune Marco Cuturi 132 0 0 13 Mar 2025
On the query complexity of sampling from non-log-concave distributions Yuchen He Chihao Zhang 114 1 0 10 Feb 2025
CPR: Retrieval Augmented Generation for Copyright Protection Aditya Golatkar Alessandro Achille Luca Zancato Yu-Xiang Wang Ashwin Swaminathan Stefano Soatto DiffM 80 17 0 27 Mar 2024
On a Neural Implementation of Brenier's Polar Factorization Nina Vesseron Marco Cuturi 119 2 0 05 Mar 2024
Implicit Diffusion: Efficient Optimization through Stochastic Sampling Pierre Marion Anna Korba Peter Bartlett Mathieu Blondel Valentin De Bortoli Arnaud Doucet Felipe Llinares-López Courtney Paquette Quentin Berthet 154 15 0 08 Feb 2024
The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks S. Bieringer Gregor Kasieczka Maximilian F. Steffen Mathias Trabs 87 1 0 13 Oct 2023
Particle Mean Field Variational Bayes Minh-Ngoc Tran Paco Tseng Robert Kohn 77 3 0 24 Mar 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 64 6 0 08 Mar 2023
Asynchronous Bayesian Learning over a Network Kinjal Bhar H. Bai Jemin George Carl E. Busart FedML 56 0 0 16 Nov 2022
Self-Adapting Noise-Contrastive Estimation for Energy-Based Models Na Xu 17 2 0 03 Nov 2022
Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling Jacopo Guidolin Vyacheslav Kungurtsev Ondvrej Kuvzelka BDL 38 0 0 02 Nov 2022
Denoising MCMC for Accelerating Diffusion-Based Generative Models Beomsu Kim Jong Chul Ye DiffM 93 15 0 29 Sep 2022
$A Particle-Based Algorithm for Distributional Optimization on \textit{Constrained Domains} via Variational Transport and Mirror Descent$ A Particle-Based Algorithm for Distributional Optimization on \textit{Constrained Domains} via Variational Transport and Mirror Descent Dai Hai Nguyen Tetsuya Sakurai 100 2 0 01 Aug 2022
Discrete Langevin Sampler via Wasserstein Gradient Flow Haoran Sun H. Dai Bo Dai Haomin Zhou Dale Schuurmans BDL 90 24 0 29 Jun 2022
Convergence for score-based generative modeling with polynomial complexity Holden Lee Jianfeng Lu Yixin Tan DiffM 80 140 0 13 Jun 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 88 19 0 01 Jun 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 104 18 0 28 Feb 2022
Unadjusted Langevin algorithm for sampling a mixture of weakly smooth potentials D. Nguyen 58 5 0 17 Dec 2021
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 167 57 0 04 Dec 2021
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees Oren Mangoubi Nisheeth K. Vishnoi 83 15 0 07 Nov 2021
A Proximal Algorithm for Sampling from Non-smooth Potentials Jiaming Liang Yongxin Chen 108 26 0 09 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 72 16 0 05 Oct 2021
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling Keru Wu S. Schmidler Yuansi Chen 127 54 0 27 Sep 2021
Sqrt(d) Dimension Dependence of Langevin Monte Carlo Ruilin Li H. Zha Molei Tao 94 29 0 08 Sep 2021
Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity Yuling Jiao Lican Kang Yanyan Liu Youzhou Zhou OT 53 6 0 10 Jul 2021
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity Jian Huang Yuling Jiao Lican Kang Xu Liao Jin Liu Yanyan Liu 98 27 0 21 Jun 2021
Stochastic Gradient Langevin Dynamics with Variance Reduction Zhishen Huang Stephen Becker 82 7 0 12 Feb 2021
Unadjusted Langevin algorithm for non-convex weakly smooth potentials D. Nguyen Xin Dang Yixin Chen 78 14 0 16 Jan 2021
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate Analysis Atsushi Nitanda Denny Wu Taiji Suzuki 86 29 0 31 Dec 2020
Policy Optimization as Online Learning with Mediator Feedback Alberto Maria Metelli Matteo Papini P. DÓro Marcello Restelli OffRL 54 10 0 15 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
Efficient constrained sampling via the mirror-Langevin algorithm Kwangjun Ahn Sinho Chewi 117 57 0 30 Oct 2020
Riemannian Langevin Algorithm for Solving Semidefinite Programs Mufan Li Murat A. Erdogdu 118 29 0 21 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
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm Adil Salim Peter Richtárik 78 40 0 16 Jun 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence Sinho Chewi Thibaut Le Gouic Chen Lu Tyler Maunu Philippe Rigollet 100 70 0 03 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
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
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
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 141 49 0 04 Nov 2019
Aggregated Gradient Langevin Dynamics Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 81 1 0 21 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
Bayesian Robustness: A Nonasymptotic Viewpoint Kush S. Bhatia Yian Ma Anca Dragan Peter L. Bartlett Michael I. Jordan 46 7 0 27 Jul 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
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
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 105 43 0 30 May 2019