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Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization

20 July 2017

Quanquan Gu

Papers citing "Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization"

50 / 97 papers shown

Title
Regime-Switching Langevin Monte Carlo Algorithms Xiaoyu Wang Yingli Wang Lingjiong Zhu 12 0 0 31 Aug 2025
From Global to Local: A Scalable Benchmark for Local Posterior Sampling Rohan Hitchcock Jesse Hoogland 42 0 0 29 Jul 2025
Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown Emile Anand Sarah Liaw 60 0 0 21 Jul 2025
Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Jacob K Christopher Michael Cardei Jinhao Liang Ferdinando Fioretto DiffM MedIm 101 1 0 01 Jun 2025
Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management Yi-Hu Feng Tianlin Li Tian Xie 142 0 0 26 Feb 2025
Training-Free Constrained Generation With Stable Diffusion Models Stefano Zampini Jacob K Christopher Luca Oneto Davide Anguita Ferdinando Fioretto 147 4 0 08 Feb 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 218 4 0 28 Jan 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 566 1 0 08 Oct 2024
Energy-based Hopfield Boosting for Out-of-Distribution Detection Claus Hofmann Simon Schmid Bernhard Lehner Daniel Klotz Sepp Hochreiter OODD 227 10 0 14 May 2024
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo Haoyang Zheng Wei Deng Christian Moya Guang Lin 152 7 0 22 Jan 2024
Communication-Efficient Federated Non-Linear Bandit Optimization Chuanhao Li Chong Liu Yu Wang FedML 83 1 0 03 Nov 2023
Langevin Quasi-Monte Carlo Sifan Liu BDL 74 4 0 22 Sep 2023
Riemannian Langevin Monte Carlo schemes for sampling PSD matrices with fixed rank Tianmin Yu Shixin Zheng Jianfeng Lu Govind Menon Xiangxiong Zhang 51 0 0 08 Sep 2023
Gradient is All You Need? Konstantin Riedl T. Klock Carina Geldhauser M. Fornasier 110 9 0 16 Jun 2023
Stochastic Gradient Langevin Dynamics Based on Quantization with Increasing Resolution Jinwuk Seok Chang-Jae Cho 86 0 0 30 May 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 141 24 0 29 May 2023
Subsampling Error in Stochastic Gradient Langevin Diffusions Kexin Jin Chenguang Liu J. Latz 107 0 0 23 May 2023
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms Shogo H. Nakakita 122 0 0 22 Mar 2023
Guiding Energy-based Models via Contrastive Latent Variables Hankook Lee Jongheon Jeong Sejun Park Jinwoo Shin BDL 127 16 0 06 Mar 2023
Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization Junlong Lyu Zhitang Chen Wenlong Lyu Jianye Hao 29 0 0 30 Jan 2023
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions Marelys Crespo Navas S. Gadat X. Gendre 103 0 0 08 Jan 2023
Non-reversible Parallel Tempering for Deep Posterior Approximation Wei Deng Qian Zhang Qi Feng F. Liang Guang Lin 101 4 0 20 Nov 2022
Asynchronous Bayesian Learning over a Network Kinjal Bhar H. Bai Jemin George Carl E. Busart FedML 79 0 0 16 Nov 2022
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 118 4 0 25 Oct 2022
$Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient$ Langevin dynamics based algorithm e-TH $\varepsilon$ O POULA for stochastic optimization problems with discontinuous stochastic gradient Dongjae Lim Ariel Neufeld Sotirios Sabanis Ying Zhang 110 7 0 24 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 133 15 0 05 Oct 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 122 2 0 01 Aug 2022
Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting Ariel Neufeld Matthew Ng Cheng En Ying Zhang 123 13 0 06 Jul 2022
Langevin Monte Carlo for Contextual Bandits Pan Xu Hongkai Zheng Eric Mazumdar Kamyar Azizzadenesheli Anima Anandkumar 102 29 0 22 Jun 2022
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems Giannis Daras Y. Dagan A. Dimakis C. Daskalakis BDL 163 15 0 18 Jun 2022
Constrained Langevin Algorithms with L-mixing External Random Variables Yu Zheng Andrew G. Lamperski 112 6 0 27 May 2022
Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization Yuri Kinoshita Taiji Suzuki 142 18 0 30 Mar 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 134 68 0 10 Feb 2022
STOPS: Short-Term-based Volatility-controlled Policy Search and its Global Convergence Liang Xu Daoming Lyu Yangchen Pan Aiwen Jiang Bo Liu 145 0 0 24 Jan 2022
Global convergence of optimized adaptive importance samplers Ömer Deniz Akyildiz 142 7 0 02 Jan 2022
Unadjusted Langevin algorithm for sampling a mixture of weakly smooth potentials D. Nguyen 87 6 0 17 Dec 2021
Time-independent Generalization Bounds for SGLD in Non-convex Settings Tyler Farghly Patrick Rebeschini 130 25 0 25 Nov 2021
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization Fu Wei Chenglong Bao Yang Liu 85 20 0 04 Oct 2021
Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function Dongjae Lim Ariel Neufeld Sotirios Sabanis Ying Zhang 110 20 0 19 Jul 2021
Revisiting the Effects of Stochasticity for Hamiltonian Samplers Giulio Franzese Dimitrios Milios Maurizio Filippone Pietro Michiardi 73 3 0 30 Jun 2021
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks Dong-Young Lim Sotirios Sabanis 130 12 0 28 May 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 91 18 0 06 May 2021
Stochastic Gradient Langevin Dynamics with Variance Reduction Zhishen Huang Stephen Becker 100 9 0 12 Feb 2021
Higher Order Generalization Error for First Order Discretization of Langevin Diffusion Mufan Li Maxime Gazeau 64 1 0 11 Feb 2021
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels Hao Wang Rui Gao Flavio du Pin Calmon 154 18 0 05 Feb 2021
Unadjusted Langevin algorithm for non-convex weakly smooth potentials D. Nguyen Xin Dang Yixin Chen 86 16 0 16 Jan 2021
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate Analysis Atsushi Nitanda Denny Wu Taiji Suzuki 202 31 0 31 Dec 2020
Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning Andrew G. Lamperski 75 29 0 22 Dec 2020
Recent Theoretical Advances in Non-Convex Optimization Marina Danilova Pavel Dvurechensky Alexander Gasnikov Eduard A. Gorbunov Sergey Guminov Dmitry Kamzolov Innokentiy Shibaev 165 88 0 11 Dec 2020
Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods Taiji Suzuki Shunta Akiyama MLT 93 12 0 06 Dec 2020